# Tweets from the Campaign Trail

Alexander Frame, Arnaud Mercier, Gilles Brachotte, Caja Thimm

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Alexander Frame, Arnaud Mercier, Gilles Brachotte, Caja Thimm. Tweets from the Campaign Trail: Researching Candidates' Use of Twitter during the European Parliamentary Elections. Alex Frame; Arnaud Mercier; Gilles Brachotte; Caja Thimm. Peter Lang, 11, pp.274, 2016, Bonner Beiträge zur Medienwissenschaft, 978-3-631-67009-5. 10.3726/978-3-653-06168-0. halshs-01239117

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Alex Frame / Arnaud Mercier / Gilles Brachotte / Caja Thimm (eds.)

# Tweets from the Campaign Trail

## Researching Candidates' Use of Twitter
During the European Parliamentary Elections

Bonner Beiträge zur Medienwissenschaft
Band 11

Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm - 978-3-631-69740-5

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ACADEMIC RESEARCH
Hailed by many as a game-changer in political communication, Twitter has made its way into election campaigns all around the world. The European Parliamentary elections, taking place simultaneously in 28 countries, give us a unique comparative vision of the way the tool is used by candidates in different national contexts. This volume is the fruit of a research project bringing together scholars from 6 countries, specialised in communication science, media studies, linguistics and computer science. It seeks to characterise the way Twitter was used during the 2014 European election campaign, providing insights into communication styles and strategies observed in different languages and outlining methodological solutions for collecting and analysing political tweets in an electoral context.

Alex Frame is Associate Professor in Communication Science at the University of Burgundy (Dijon) where he works within the TIL research group (EA4182).

Arnaud Mercier is Professor in Communication Science and member of the French Press Institute (IFP, Paris).

Gilles Brachotte is Associate Professor in Communication Science at the University of Burgundy (Dijon) and member of the CIMEOS-3S research group (EA4177).

Caja Thimm is Professor in Media Studies and Intermediality at the University of Bonn.
Tweets from the Campaign Trail
Bonner Beiträge zur Medienwissenschaft

Edited by Caja Thimm

Volume 11
# Tweets from the Campaign Trail

## Researching Candidates' Use of Twitter During the European Parliamentary Elections
## Bibliographic Information published by the Deutsche Nationalbibliothek

The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the internet at http://dnb.d-nb.de.

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## Library of Congress Cataloging-in-Publication Data

Names: Frame, Alex, 1976- editor.

Title: Tweets from the campaign trail: researching candidates' use of Twitter during the European parliamentary elections / Alex Frame, Arnaud Mercier, Gilles Brachotte, Caja Thimm (eds.).

Description: Frankfurt am Main : Peter Lang, 2016. | Series: Bonner Beiträge zur Medienwissenschaft ; Volume 11

Identifiers: LCCN 2016043861 | ISBN 9783631670095 | ISBN 9783653061680 (E-Book) | ISBN 9783631697405 (EPUB) | ISBN 9783631697412 (MOBI)

Subjects: LCSH: European Parliament--Elections--2014. | Twitter--Political aspects--European Union countries. | Social media--Political aspects--European Union countries. | Communication in politics--Technological innovations--European Union countries.

Classification: LCC JN36.T94 2016 | DDC 324.94/05612--dc23 LC record available at https://lccn.loc.gov/201604386

Umschlaggestaltung: Nina Adams
Gefördert durch das DFG-Schwerpunktprogramm 1505 "Mediatisierte Welten"

DFG

Deutsche
Forschungsgemeinschaft

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DFG priority program 1505
MEDIATIZED WORLDS

ISSN 16178432

ISBN 978-3-631-67009-5 (Print)

E-ISBN 978-3-653-06168-0 (E-Book)

E-ISBN 978-3-631-69740-5 (EPUB)

E-ISBN 978-3-631-69741-2 (MOBI)

DOI 10.3726/978-3-653-06168-0

© Peter Lang GmbH

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Frankfurt am Main 2016

PL Academic Research is an Imprint of Peter Lang GmbH.

Peter Lang - Frankfurt am Main · Bern · Bruxelles · New York ·

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Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm · 978-3-631-69740-5

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# Contents

<table><tr><td>Alex Frame, Arnaud Mercier, Gilles Brachotte & Caja Thimm<br>General Introduction</td><td>7</td></tr></table>

## Part 1: Studying Tweet campaigns: methodological issues

Éric Leclercq, Marinette Savonnet, Thierry Grison, Sergey Kirgizov & Ian Basaille

1. SNFreezer: a Platform for Harvesting and Storing Tweets in a Big Data Context..................................................................................................................19

Dario Compagno

2. Families of practices. A bottom-up approach to differentiate how French candidates made use of Twitter during the 2014 European Campaign..................................................................................................................33

Tatiana Kondrashova & Alex Frame

3. Exploring the dialogical dimension of political tweets: A qualitative analysis of 'Twitter styles' of UK candidates during the 2014 EU Parliamentary Elections ..................................................................................................................53

Nanta Novello Paglianti

4. Twitter et la politique : stratégies de communication de candidats et espace public..................................................................................................................75

## Part 2: Tweet campaign argumentation

Arnaud Mercier

5. Les figures de l'ennemi dans les tweets-polémiques des forces protestataires françaises durant la campagne de mai 2014..................................................101

Marina Villa

6. Les discours sur l'Europe dans la tweet-campagne en Italie ..................................................121

Elena Albu

7. Love Britain? Vote UKIP! The Pragmatics of Electoral Tweets during the European Elections 2014 ..................................................................................................................145
**General Introduction**

In the course of the past six to eight years, Twitter has rapidly imposed itself as one of the major digital PR tools used by politicians in many countries around the world, and in several cases, politicians and journalists have been early adopters (Grant, Moon, & Busby Grant, 2010). Much research carried out into the kinds of information tweeted by politicians, in various countries, suggests that the tool is often used by politicians principally for self-promotion, especially during electoral periods, in the traditional top-down style of political communication (Grant et al., 2010; Larsson & Kalsnes, 2014). As such, Twitter provides new impetus to the *personalization of politics* especially as its design, affordances and network structure allow politicians to “expand the political arena for increased personalized campaigning” (Enli & Skogerbø, 2013: 758). One reason for politicians’ self-presentation practices on Twitter is that of ‘easy marketing’: Especially during election times, candidates who have a Twitter presence are more likely to post their own messages rather than relying on a “well-resourced media staff” (Bruns & Highfield, 2013: 669). In the context of local campaigns, social media can also be used to promote the action of militants and to recruit new ones. The candidate congratulates them publicly, often by retweeting their messages and pictures (Mercier, 2015). In addition, Twitter’s functionality as a dynamic information distribution tool offers politicians the possibility to cross-promote and shape their online-identities, for example by linking to their personal blogs, Facebook pages or an online-newspaper article about them (Enli & Skogerbø, 2013).

Twitter’s information and networking function, which make political (self-) marketing opportune, is also seen as a key factor for politicians when interacting with others – especially on the institutional level. Strategic exchange with journalists, bloggers or fellow politicians is a central practice of politicians’ Twitter activity during election times (Nuernbergk & Conrad, 2016; Thimm, Anastasiadis, Bürger & Einspänner, 2014). In this context, several studies raise the concern that Twitter develops into an exclusive medium, which is–against the hopes of “e-democracy-enthusiasts”–mainly used among a well informed and well educated online-elite (Grant et al., 2010; Block, 2013; Ekman & Widholm, 2015) and thus reflects power inequalities known from the pre-internet era (Gerhards & Schäfer, 2010; Carpentier, 2012). However, while networks between “informed elites” like politicians and journalists on Twitter can be described as close, they are “not
closed” (Verweij, 2012: 690): On the one hand, the Twitter public sphere seems to be dominated by the politically interested and engaged but on the other hand, “its influence extends far beyond” (Grant et al., 2010: 599). This means that one has to take into account the role of the passive participants on Twitter, so-called lurkers, who may not actively tweet or retweet but who read along and gather information relevant for their own deliberative processes. Yet Twitter research in this area still is an intention (e.g., Bechmann & Lomborg, 2013; Himmelboim, McCreery & Smith, 2013), as mapping and profiling “passive” audiences on social media is a difficult task. Moreover, between political elites and the passive audience, there is a category of Twitter users for whom the network is a tool for unconventional political participation. Derision towards the rulers and political forces, media criticism and the development of more participatory forms of engagement, are all ways of using Twitter as a counter public sphere (Mercier, 2016), and which often appear problematic to politicians and their staff.

Therefore, the focus of current political Twitter research is on the detectable, like structures and practices of politicians' and users' interaction. A central question in fact is that of Twitter as a more direct platform for dialogical communication between politicians and their voters; thus it is a question of Twitter's potential as a tool for digital democracy. While politicians themselves often claim (or report an idealistic motivation) to use social media like Twitter for connecting with voters and discuss politics with them, studies show that they actually seldom manage to interact with them in practice (Enli & Skogerbø, 2013, Frame & Brachotte (eds), 2015, Thimm et al., 2016). Twitter has, up until now, only rarely been used by politicians to exchange information, debate or give insights into political processes (Golbeck, Grimes, & Rogers, 2010; Lawless, 2012; Vergeer & Hermans, 2013). However, some authors have found evidence of differing styles of Twitter use among politicians, depending on their personal profile (Dang-Anh, Einspänner, & Thimm, 2012; Thimm et al. 2016; Jackson & Lilleker, 2011; Sæbø, 2011) and others have proposed evidence of maturing patterns of usage (Frame & Brachotte, 2013; Grant et al., 2010), cross-media usage (Mercier, 2013) and of the influence of a small political elite within a national Twittersphere (Ausserhofer & Maireder, 2013; Grant et al., 2010).

All in all, the *mediatization of politics* (Block, 2013; Esser & Strömbäck, 2014; Thimm, Dang-Anh & Einspänner, 2014) and the underlying developments like politicians' ubiquitous media presence, the high availability of political information and the various possibilities for “micro-participation” online might suggest an overall better accessibility of and interest in politics. However, when looked at the facts that testify “real political participation”, i.e., voter turnout, the low
numbers in some western societies prove otherwise (Franklin, 2004; Blais, 2006). Reasons for increasing or decreasing voter turnout over time in various countries are mainly due to different variables like the respective voting system, voting age and rules (Franklin, 2004). While those institutional variables are set, much focus nowadays is on the practical question of how to mobilize voters and increase voter turnout – in short: on candidates’ campaigning efforts. The importance of a sophisticated campaigning strategy especially becomes visible in the US presidential elections, where candidates (and their campaign teams) virtuously employ all sorts of online and offline media in order to mobilize their voters (Burton, Miller & Shea, 2015; Benoit, 2016).

The European parliamentary elections can be considered a particular challenge for political candidates (Maarek, 2012), as EU elections in general attract less attention among media and citizens than national elections (De Vreese, Banducci, Semetko, & Boomgaarden, 2006). In 2009, overall voter turnout averaged a mere 43 % of over 375 million eligible European citizens. The 2014 EU elections even had the lowest voter turnout on record with 42.5 % (euroactiv.com) although it has been the largest election for the European Parliament that has ever been held with over 12,000 candidates from almost 450 parties from 28 member states (Treib, 2014). In the absence of a clearly distinguishable European public sphere (Dacheux 2003; De Wilde, Michailidou & Trenz, 2014), getting citizens to discuss European issues, rather than domestic ones, often appears a particularly delicate task. Tendencies of fragmentation became especially vivid in the run-up to the 2014 elections, where many anti-European voices made themselves heard. While Eurosceptic parties won seats in the Parliament in 23 out of the 28 member states, however, it has to be distinguished between “hard and soft Euroscepticism” (Treib, 2014: 1543): The former rejects the whole idea of the European Union in principle, the latter accept the idea of the EU project but oppose specific policies of the EU. Eurosceptic parties are found within the whole political spectrum—from the radical left and centrist to moderate right and radical right (Treib, 2014).

The use of social media and Twitter in particular has been an important asset during the European elections for all candidates, but especially for Eurosceptic parties. A study of over 1.2 million tweets sent in English, French, and German during the EU elections 2014 suggests that national parties “with an explicitly anti-EU or anti-Euro platform generated the most attention” (Pew Research Center, 2014). When looking at the campaigning strategies of selected candidates from Eurosceptic parties a great networking effort can be observed: Marine Le Pen from the French Front National for example tries to restrict her Twitter followers to party members and supportive voices (Thimm et al., 2016). Also, the German
Eurosceptic party Alternative for Germany (AfD) tries a more informative than dialogical way of tweeting (ibid.). Overall, current Twitter research gives the impression of highly diverse patterns of individual tweeting strategies among EU candidates, but for the prospective representatives of an institution often portrayed in European media as being distant from domestic voters, Twitter and other social media can at least be used to give the image (rightly or wrongly) of a tool cutting across barriers and favouring direct communication with voters. However, politicians need to be aware of the dangers of using the participatory features of Twitter in a purely cosmetic way. Already the renewal of democracy through participatory procedures was a promise most often not fulfilled. They must be careful not to create additional democratic disenchantment with social networks.

**This volume: Twitter as a political practice**

This volume is a collection of papers which examine the way Twitter was used by candidates from different countries, during the 2014 European Parliamentary Election campaign. All of the contributors took part in an international research project to compare Twitter use during these elections in five different countries: Belgium, France, Germany, Italy, Spain and the United Kingdom. All of the tweets sent by or to all of the candidates in these countries were collected during a month around the election date, as well as others which mentioned the candidates themselves, or used hashtags associated with the elections. On the basis of the 50 million tweets collected, processed and divided into national corpora, the different teams worked to establish the specificities of Twitter usage between candidates, parties and countries, looking at a whole range of aspects and of research questions. The current volume brings together the first set of results from the project.

The book has been designed to interest researchers or academics studying the way Twitter is used during European or other elections. Since the project team brings together colleagues working in communication studies, political science and computer science, it has developed integrated solutions and methodologies for collecting and studying Twitter data, using various qualitative and quantitative techniques. The volume builds on the experience of the project team to highlight the difficulties encountered when conducting this kind of research, and how they were overcome. Thus it presents methodological discussions and solutions (Part 1), as well as more theoretical parts dedicated to argumentation styles (Part 2) and political communication strategies in the various countries (Part 3).

In the first chapter of the section outlining methodological challenges and solutions to studying the use of Twitter during political campaigns, Éric Leclercq, Marinette Savonnet, Thierry Grison, Sergey Kirgizov and Ian Basaille outline
some of the difficulties encountered in developing SNFreezer, the open source
tool which they produced and integrated as a platform to help researchers col-
lect, store and analyse large quantities of tweets. Written from a computer sci-
ence perspective, the chapter discusses the technical constraints faced by teams
seeking to capture numerous posts via Twitter's programming interface, and ex-
plains how a multi-paradigm platform can fulfill the requirements of building
a corpus of tweets (selecting, harvesting and storing tweets) and can reduce the
waiting time for researchers to perform analysis on data. It highlights issues such
as the scalability of the architecture that is collecting tweets, as well as its failover
mechanism. The originality of this approach is to combine concerns about data
harvesting, data storage and data analysis into one platform. The resulting polyglot
storage system supports a relational database, graph database or structured files
and a set of tools that can provide a suitable solution for mixing different types
of algorithms in order to maximize knowledge extraction. The chapter describes
the software architecture of the platform and shows how it uses the Twitter APIs
and how end-users can select the best data model according to their analysis.

In chapter two, Dario Compagno outlines a mixed methods approach to ana-
lysing “families of practices” based on Twitter use by different French candidates
during the 2014 European campaign. The approach used here is to apply unsu-
pervised learning techniques to let clusters of candidates emerge from the Twitter
data, using operators interpreted by Twitter (hashtags, retweets, hyperlinks, men-
tions) as variables for clustering. The chapter gives details of the families of uses
identified in this way: for example, while some candidates prefer to tweet links
to online resources, therefore recognizing the informative potential of the social
platform, others tweet many more mentions than links, in a sort of relational
“style”. It could be inferred that candidates belonging to different families of uses
conceive Twitter differently.

In the third chapter, Tatiana Kondrashova and Alex Frame take previous work
done on “Twitter Styles” as a starting point to develop a conceptual model seeking
to qualify the “dialogical dimension of political tweets”. This approach is based on
a qualitative analysis applied to the UK corpus, taking into account the notion of
“reach” in order to discuss political use of Twitter without simply referring to the
traditional and sometimes misleading categories of “informative vs interactive”.
Chapter 4, written by Nanta Novello Paglianti, looks qualitatively into the use of
Twitter by selected Italian candidates during the campaign, in order to character-
ise the communication strategies adopted, and to seek to define the form of the
contemporary political tweet.
The second part of the volume focuses more precisely on forms of argumen-
tation on Twitter. Chapters 5 and 6 both address the question of the rhetorical
construction of the Other in campaign discourse on Twitter. In chapter 5, Arnaud
Mercier analyses the French corpus from the angle of different figures of “the
enemy” in the pro- or anti-European context, and Marina Villa presents similar
results for the Italian corpus in the following chapter. They emphasize the po-
lemical usage that candidates make of tweets and underline the strong homology
between electoral tweets, and soundbites produced for traditional media.

Elena Albu adopts a linguistic approach to political tweets in chapter 7, ex-
amining the various ways in which candidates from the UK Independence Party
use calls to action in their tweets, via the #VoteUKIP hashtag. By studying the
linguistic strategies and grammatical forms associated with these calls to vote,
the chapter identifies the importance of the position of the hashtag and its ac-
companying elements in influencing its apparent function in individual tweets.
The author highlights differences between informative and argumentative calls
to action, establishing a typology which allows her to characterise the tweets ac-
cording to how explicitly and directly the reason for voting UKIP is presented.

The articles in the third part of the book look more generally at the ways in
which Twitter has been integrated into the political communication strategies
of candidates in four of the countries studied. In chapter 8, Gilles Brachotte and
Frédéric Junger provide a quantitative overview of data in order to discuss and
characterise the way the microblogging platform was used in the French context
by the different parties in competition during the European elections and by in-
dividual candidates, in order to differentiate them based on their Twitter metrics
and the underlying patterns of usage.

Caja Thimm, Jessica Einspänner Pflock and Mario Anastasiadis discuss the
results of their analysis of the German corpus in chapter 9. They discuss the af-
fordances of Twitter for political discourse with a focus on Twitter usage during
the EU elections in Germany. The quantitative and qualitative analyses of tweets
collected during a specified period of four weeks were carried out on the basis of
the functional operator model of Twitter. The model serves as a framework for
assessing users' tweeting styles, which can range between personal-interactive and
topical-informative. They show the differences between individual politainment
strategies but do also question the candidates' alleged efforts to enter into dialogue
with their voters. The authors conclude that politicians used Twitter during the EU
election mainly as a tool for self-marketing and establishing themselves within a
communication infrastructure of their own, outside traditional media.
Vittorio Cobianchi, Maria Francesca Murru and Marina Villa, in chapter 10, look more precisely at the question of Twitter use as “second screen” during tel-evised political debates in Italy. A content analysis of tweets created by politi-cal parties before and during the appearance of their candidates on TV shows Twitter’s function as a tool to amplify and multiply political messages conveyed through the medium of television. In addition, an analysis of the tweets created by the Twitter audience during the broadcast of the Italian talk show “Porta a Porta” underpins the hypothesis that second screen communication on Twitter conveys patterns of self-representation and opinion stating, especially against or in support of the political candidates on TV.

Finally, in chapter 11, Fernando Bonete Vizcaino, Elena Cebrián Guinovart and Tamara Vázquez Barrio focus on the use of Twitter by the leader of the Spanish political formation Podemos, Pablo Iglesias. They ask to what degree the promise of renewal in politics and political discourse which this new formation embodies can be detected in the use of Twitter by its leader. They take into consideration Iglesias’s tweets, the main themes addressed and the comments received in order to offer a detailed analysis of this particular leader’s political communication strategy on Twitter.

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De Vreese, C. H., Banducci, S. A., Semetko, H. A., Boomgaarden, H. G., 2006. The News Coverage of the 2004 European Parliamentary Election Campaign in 25 Countries. *European Union Politics*, 7(4), 477–504.

De Wilde, P., Michailidou, A. & Trenz, H.-J. (2014). Converging on euroscepti-cism: Online polity contestation during European Parliament elections. *European Journal of Political Research* 53, 766–783.

**Online Sources:**

Euroactiv.com: *It's official: Last EU election had lowest-ever turnout*. http://www.euractiv.com/section/eu-elections-2014/news/it-s-official-last-eu-election-had-lowest-ever-turnout/.

Pew Research Center (2014). *The EU Elections on Twitter. Mixed Views about the EU & Little Passion for the Candidates*. http://www.journalism.org/2014/05/22/the-eu-elections-on-twitter/.
Part 1:
Studying Tweet campaigns:
methodological issues
Éric Leclercq, Marinette Savonnet, Thierry Grison,
Sergey Kirgizov & Ian Basaille, Laboratoire LE2I - UMR6306 -
CNRS - ENSAM, Univ. Bourgogne Franche-Comté

# 1. SNFreezer: a Platform for Harvesting and Storing Tweets in a Big Data Context

**Abstract**

In this chapter we show how a multi-paradigm platform can fulfill the requirements of building a corpus of tweets and can reduce the waiting time for researchers to perform analysis on data. We highlight major issues such as the scalability of the architecture that is collecting tweets, as well as its failover mechanism.

## 1.1 Introduction and Objectives

In general, analysing complex interaction networks including Twitter data requires different types of algorithms with different theoretical foundations such as graph theory, linear algebra, or statistical models. Regarding tweet analysis, intrinsic links built by operators (i.e. hashtags denoted by #, user mentions denoted by @, reply, and retweets) have a strong impact on the data model and on the performances of the algorithms being used.

Addressing a scientific question often requires mixing different classes of algorithms using different data models that retrieve data from different storage structures. For instance, graph-based algorithms using a matrix adjacency representation are useful for discovering community structure; a Laplacian matrix is useful to evaluate centrality. In general, graph-based algorithms are near-sighted, they do not take into account contextual information. Linear algebra algorithms can be used to identify large scaled structures, for instance clusters can be found using Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). Machine learning algorithms and statistical models are used to predict links or behaviors, to detect anomalies or events. In a context of massive datasets, the most efficient storage structure should be used according to the selected algorithms, knowing that different kinds of algorithms are usually mandatory.

Analysis of tweets can be performed at different levels of granularity: at an individual level like influence assessment, sentiment analysis, by extraction of features that are not explicit; and at a corpus level, through emergence of groups
of users exhibiting similar behavior. Thus, possible outcomes of the analysis are
the discovery of social structures, social positions, i.e. the role of individuals.

Our contribution is an open source platform named SNFreezer (https://github.com/SNFreezer) that supports the management and the analysis of social data with different paradigms. We have developed a polyglot storage system to store and retrieve tweets in different structures that are able to scale up to the data flow requirements.

## 1.2 New Paradigms for Data Management Systems

Most enterprise business applications rely on relational database management
systems (RDBMS). This technology is mature, widely understood and adapted.
However, some issues have recently emerged:

* RDBMS may not have adequate performance for massive datasets;

* RDBMS cannot provide the scalability required by online social network applications;

* The structure of the relational model can be too rigid or not relevant to deal with the variability of complex data networks;

* SQL was not designed to perform explanatory data analysis queries which does not provide exact results.

Explicit and implicit links between social data can also be a hindrance to the use of RDBMS if they are combined with massive data. Explicit links are usually used by path queries that require joining tables, but when the length of the path is not known, SQL often needs to be embedded in a programming language. Implicit links can be discovered by data analysis but the schema of the relational database cannot be quickly and easily updated according to newly discovered relationships.

Considering these drawbacks, a number of systems, not following the relational model paradigms, have recently emerged. They are often denoted under the umbrella term of NoSQL databases (Moniruzzaman 2013).

In general, NoSQL databases rely on schema-less data models and scale horizontally. Their common features are scalability and flexibility in the structure of data. NoSQL database management systems provide different solutions for specific problems: the volume of datasets is addressed in the column-oriented NoSQL or key-value (HBase<fnref n="1" />, Cassandra<fnref n="2" />); documents and links management is supported

<footnote n="1">1 http://hbase.apache.org/</footnote>

<footnote n="2">2 http://cassandra.apache.org/</footnote>
by document databases (CouchDB<fnref n="3" />, MongoDB<fnref n="4" />); high density of links, nodes and properties are taken into account in graph database management systems (GDBMS) which are also ideal for performing queries that walk down hierarchical relationships (Neo4j<fnref n="5" />, HypergraphDB<fnref n="6" />). XML oriented databases provide a highly extensible data model but lack scalability in the context of social networks.

NoSQL databases can be accessed by different APIs and different query languages, so Atzeni and al. (2014) propose a common programming interface to NoSQL systems hiding the specification details of the various systems for developing applications. The TinkerPop project<fnref n="7" /> adopts a similar approach for graph databases. It introduces a graph query language, Gremlin, which is a domain-specific language based on Groovy<fnref n="8" />, supported by most GDBMS. Unlike most query languages that are declarative, Gremlin is an imperative language focusing on graph traversals.

The multi-paradigm principle tends to generalize these different approaches. In modelling, multi-paradigm approaches address the necessity of using multiple modelling paradigms to design complex systems (Hodge et al. 2011). Indeed, complex systems require the use of multiple modelling languages to: 1) cope with the inherent heterogeneity of such systems; 2) offer different points of view on all their relevant aspects; 3) cover different activities of the design cycle; 4) allow reasoning at different levels of detail during the design process (Hardebolle and Boulanger 2009). As a result, multi-paradigm modelling addresses three orthogonal directions of research: 1) multi-formalism modelling, concerned with the coupling and transformation between models described in different formalisms; 2) model abstraction concerned with the relationship between models at different levels of abstraction; 3) meta-modelling concerned with the description of classes of models dedicated to particular domains or applications called Domain Specific Languages (DSL). Multi-paradigm data storage or polyglot persistence uses multiple data storage technologies, chosen according to the way data is used by applications and/or algorithms (Sharp et al. 2013). As Ghosh states in (Ghosh 2010), storing data the way it is used in an application simplifies programming and makes it easier to decentralize data processing. ExSchema (Castrejon et al. 2013) is a tool that enables automatic discovery of data schema from a system that relies on multiple documents, graph, relational, column-family data stores.

<footnote n="3">3 http://couchdb.apache.org/</footnote>

<footnote n="4">4 https://www.mongodb.org/</footnote>

<footnote n="5">5 http://neo4j.com/</footnote>

<footnote n="6">6 http://hypergraphdb.org/</footnote>

<footnote n="7">7 http://www.tinkerpop.com</footnote>

<footnote n="8">8 http://groovy.codehaus.org/</footnote>
## 1.3 SNFreezer Architecture

In order to collect tweets during the political campaign, we have started by analysing existing solutions and we retained the project YourTwapperKeeper<fnref n="9" /> (YTK), an open source project that claims to provide users with a tool that archives data from Twitter directly on a server. After a period of tests and code review, we identified some major drawbacks. YTK was not able to collect tweets in various languages; the choice of the database engine limits the volume of datasets; and it does not retrieve information on accounts such as the list of following/followers nor the timeline of the users. Thus, we chose to enhance YTK with a real storage layer and to add database connectors in order to allow analysis tools such as R to retrieve data directly from SNFreezer repositories.

### 1.3.1 The Storage System

To address the problem of tweet storage, both in terms of performance and interoperability (i.e. easy connection of third party tools) we have specified and developed a storage layer. The proposed polyglot persistence storage layer includes relational databases (RDBMS), a graph data store (GDBMS), and a scalable document database management system (DDBMS) that can be used simultaneously (figure 1).

<figure><img src="image_7.png" /><figcaption>Figure 1. SNFreezer architecture</figcaption></figure>

<footnote n="9">9 https://github.com/540co/yourTwapperKeeper
Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm - 978-3-631-69740-5
Téléchargé de PubFactory à 06/10/2021 11:57:11AM
via free access</footnote>
The configuration of the storage layer allows duplicating information in different storage systems according to the planned analysis so Neo4j or PostgreSQL ready to use databases are available during the collect. Developers can add their specific drivers for other storage systems. The data harvesting is provided by the data ingestion module connected to the Streaming and Search APIs of Twitter using two main processes that run continuously. Two other processes are used to collect the followers/following information at a defined frequency and to retrieve all the possible tweets from the timeline of the users. According to the needs and type of information to be analyzed, one can choose between various storage structures:

* For computing global metrics (e.g. number of tweets/retweets/mentions per user), a relational schema in PostgreSQL can be used.

* In the case of high traffic, it is preferable to store information in a non-normalized database scheme (one table for tweets and a few others for followers) or in JSON files or in MongoDB.

* In the case of the study of linked information (for example social network type data structure), a Neo4j graph database is suitable.

The choice of storage backend can be cumulative (both relational normalized databases and JSON files for example). We also propose a set of tools that implement model transformation to asynchronously transform data from one storage system to another.

### 1.3.2 Storing Tweets

Tweets coming through the Twitter APIs are JSON strings<fnref n="10" /> that contain information on the tweet itself, but also the user who sends or retweets (table 1). JSON strings can be stored in MongoDB or directly in the filesystem.

<caption>Table 1: Example of a tweet in JSON</caption>

[ created_at ] => Mon May 05 16:58:20 +0000 2014

[id] => 463362068553674752

[ id_str ] => 463362068553674752

[ text ] => RT @JeunesavecBLM : .@Bruno_LeMaire est ce soir à Thionville pour un meeting avec @Nadine__Morano @AnneGrommerch @ArnaudDanjean # EP2014 http...

[ source ] => <a href ="" http://twitter.com/download/iphone " rel =" nofollow " > Twitter for iPhone </a>

[ truncated ] =>

<footnote n="10">10 JSON (JavaScript Object Notation) is a lightweight data-interchange format.
Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm - 978-3-631-69740-5
Téléchargé de PubFactory à06/10/2021 11:57:11AM
via free access</footnote>
[ in reply to status id ] =>
[ in reply to status id str ] =>
[ in reply to user id ] =>
[ in reply to user id str ] =>
[ in reply to screen name ] =>
[ user ] => stdClass Object
(
[id] => 439463212
[id str ] => 439463212
[ name ] => Arnaud Danjean
[ screen name ] => ArnaudDanjean
[ location ] =>
[ description ] => Député Européen – Membre de la commission Affaires Etrangères & sous-commission Défense du Parlement Européen – Conseiller Régional de Bourgogne [ url ] => http://t.co/tOt2Mb2YUb
[ entities ] => stdClass Object .....

JSON strings are not stored directly in RDBMS (in a single attribute). First of all the
string is changed into a tuple with different attributes (one tuple = one tweet). Attrib-
utes that are extracted from this JSON string are stored in a table named gtweets. The
gtweets table contains more than 40 attributes, for example the most significant are:

* the id of the tweet (id), the content (text) and the mailing date (time), the creating time (created_at);

* the id of the twitter account who sents the tweet (from_user_id) and screen name (from_user);

* the language of the tweet (ISO_language_code), which can give an idea of the language of tweet;

* the source of the tweet (what criteria match the tweet i.e. hashtag, keyword or account)

* optional information on geolocation tweet: point, latitude, longitude (*geo_type*, *geo_coordinates_0*, *geo_coordinates_1*)

* the link to the user's profile image (*profile_image_url*)

* the id of the user the tweet replies to (if it exists) (*to_user_id*)

* the id of the tweet to which it answers (*in reply to status id*);

* the id the initial tweet if retweet (*initialtweet_id*);

* the text of the original tweet if retweet (*initial tweet text*);

* the user's initial tweet (*initialtweet_user*);

* the list of mentioned accounts (*user_mentions*);

* the list of hashtags (*hashtags*);

* the list of URLs (*urls*).
<table><caption>Table 2: An entry in gtweets according to JSON based on the example given in Table 1</caption><tr><td>flag</td><td>stream</td></tr><tr><td>text</td><td>RT @JeunesavecBLM : .@Bruno_LeMaire est ce soir à Thionville pour un meeting avec @Nadine_Morano @</td></tr><tr><td>to_user_id</td><td>AnneGrommerch @ArnaudDanjean # EP2014 http ..</td></tr><tr><td>from_user</td><td>Arnaud Danjean</td></tr><tr><td>id</td><td>463362068553674752</td></tr><tr><td>from_user_id</td><td>439463212</td></tr><tr><td>iso_language_code</td><td>fr</td></tr><tr><td>source</td><td>&lt;a href="" http://twitter.com/download/iphone " rel="" nofollow "> Twitter for iPhone </a&gt;</td></tr><tr><td>profile_image_url</td><td>http://pbs.twing.com/profile_images/1698849326/Capture_</td></tr><tr><td>geo_type</td><td>d_cran_2011-12-17_21.37.16_normal.png</td></tr><tr><td>geo_coordinates_0</td><td>0</td></tr><tr><td>geo_coordinates_1</td><td>0</td></tr><tr><td>created_at</td><td>Mon May 05 16:58:20 +0000 2014</td></tr><tr><td>time</td><td>1399309100</td></tr><tr><td>......</td><td>............</td></tr></table>

## Tweet Relational Database Schema

The *gtweets* table is complex (many attributes) and voluminous, so queries can become difficult to write. For obvious reasons of querying performance, interesting objects for data analysis are transformed and stored in separate tables (figure 2):

* The *Tweet* table contains tweets and retweeted tweets. The *Tweet* table is connected (by foreign keys) with hashtags (*Tweet_Hashtag* table), URLs (*Tweets_URL* table), symbols (*Tweet_Symbol* table) and query sources, i.e. presence of a keyword, a hashtag or an account in the tweet (*Tweet_Source* table).

* *Retweet* and *Mention* are tables that represent relationships between users and tweets. The *Retweet* table contains the user that retweeted, the id of the retweeted tweet and the date. The *Mention* table connects a tweet with the mentioned users.

* The *User* and *Identity* tables represent information about users. The *User* table represents information that cannot change in a Twitter account (*id*, *created_at*), other information can be updated by the user and are represented as an *Identity*.
<figure><img src="image_8.png" /><figcaption>Figure 2. Storing tweets in multiple relational tables</figcaption></figure>

### 1.3.3 Tweet Graph Database

In a graph database, objects (tweets, users, hashtags, etc.) are nodes with properties, and relationships are described by edges with properties (figure 3). The relationship *use* is not materialized, it may be deducted by composition. The schema has been implemented with Neo4j.

<figure><img src="image_9.png" /><figcaption>Figure 3. Storage of tweets in GDBMS</figcaption></figure>

Cypher is a query language for Neo4j, which works by using patterns on the graph database. Operators are optimized for queries requiring graphs traversal, and notably allow finding relationships between nodes despite their separation by several links (which would have required costly joins by SQL). The query in table 3 shows a simple example of what can be expressed using Cypher, here we
wish to find the identifiers of the users who retweeted '@Europarl_FR' and the number of retweets.

<caption>Table 3. A query example using Cypher</caption>

```Cypher
match (u: user) -[: USER_HAVE_IDENTITY ]->(i: identity)
where i. screen_name = '@Europarl_FR '
with distinct u as europarl_fr
match europarl_fr -[: USER_SEND_TWEET ]->(t: tweet) <-[:
USER_RETWEET_TWEET ]-(urt: user)
return urt.id, count (t);
```

The first three lines of the query request that, a user node corresponding to the identity with the screen name 'Europarl_FR' should be stored as a variable u. Line 5 retrieves Users (urt) having retweeted a tweet sent by 'Europarl_FR'. Finally, line 6 returns results grouped by user and counts, for each user, the number of his retweets.

### 1.3.4 Cluster Mode and Fail Over

Cluster and failover modes have been developed to overcome some limitations of the Streaming and Search APIs of Twitter. For instance, one application can only retrieve tweets matching one of the conditions called source query (attribute querysource in database), in a set of 400. Each account on Twitter can define applications, but for each IP address hosting the application the previous limitations apply. However, some projects require more than 400 query sources. To fulfill this requirement we have developed a cluster management module.

In the cluster mode, several virtual machines, in which instances of the data harvesting processes are deployed, can be used in a project to collect tweets using matching criteria in a set of several thousand source queries. Source queries can be defined on each virtual machine using a web interface or can be imported automatically using scripts and import files submitted to one of the virtual machines that acts as a master. In the cluster mode, it is assumed that there will be a high volume of tweets, thus the storage layer can use a non-normalized schema on PostgreSQL (gtweets table described in section 3.2), or can store data in MongoDB or in JSON files. Figure 4 gives an example of the cluster deployed to collect tweets during European Election campaign of 2014.
<figure><img src="image_10.png" /><figcaption>Figure 4. Cluster mode</figcaption></figure>

In case tweet harvesting was interrupted for any reason, the process in charge of the Search API can retrieve tweets for a period of seven days. Automatic emails are sent to the administrator with a notification of the failure (storage, networks, etc.) and when the harvesting process is restarted, the latest tweet ID is checked and the process in charge of the Search API starts collecting any lost tweets. Moreover, it is possible to include a local database on each virtual machine using MySQL as a temporary backup, and a global database using PostgreSQL.

Tools were also developed in order to monitor tweet harvesting and the instances of the different local storage in each virtual machine of the cluster. They indicate, amongst other things, the number of tweets for a given period of time, the most used hashtags or the most active users and can send alerts by email to researchers or administrators. In the case of a high volume of tweets, a replica database is used to calculate general statistics for the monitoring tools.

During the TEE2014 project this architecture allowed to harvest more than 50M tweets and the resulting database with non-normalized schema is about 50GB without indexes. For the French corpus, experiments have been performed
using Neo4j. Starting from a normalized schema of 5M tweets and a database size of 7GB we obtain a graph database of 20GB.

## 1.4 Connection with Analysis Tools and Web Applications

A specific data exchange layer is dedicated to application services, and third party tools are plugged in according to the expected analysis. Connectors have been developed to analyse data with third party software such as *R* and *igraph*<fnref n="11" /> and to display results with *D3.js*<fnref n="12" />. If a connector is not available, the layer provides export files for the different classes of algorithms such as files containing adjacency matrix, graph triple, multidimensional array or CSV (Comma-Separated Values) for spreadsheet. In the following subsection, we give some key elements for starting analysis.

In order to perform explanatory analysis on the corpus we have developed some web tools. For example, figure 5 is a component that displays the timeline of a user and shows the frequency of tweets or retweets in a period. By clicking on a point, users can display the tweet or retweet. Figure 6 depicts the interface of an algorithm to detect and characterize events. We have proposed to use a simple method that finds local minima and maxima of temporal density of tweets. This method finds the moments after which the number of published tweets begins to increase (or decrease). The method has only one parameter (bandwidth) allowing us to smoothly change the mode of the event detection: when the bandwidth is small, micro-events can be detected, and when it is large only macro-events appear. This method, by itself, does not give any description of the event, except its start and end times. Thus, in order to describe an event, we split the data using hashtag decomposition: for each hashtag of interest, we draw a temporal density plot, and we combine all these plots in the same image, which allows us to compare them. The difference in hashtag frequencies can be regarded as a first approximation of the semantic event description. A part of the program source code (detection of local minima and maxima of temporal density) is available on github<fnref n="13" />.

<footnote n="11">11 http://igraph.org/</footnote>

<footnote n="12">12 http://d3js.org/</footnote>

<footnote n="13">13 https://github.com/kerzol/changepoint-pelt-vs-timedensity</footnote>
<figure><img src="image_11.png" /><figcaption>Figure 6. A web component to detect and analyse events</figcaption></figure>

Tweets Observatory: tweets with Crimea's hashtags emmited during #EE2014

<figure><img src="image_12.png" /></figure>
## 1.5 Conclusion

In this chapter, we have presented an open framework integrating a polyglot scalable storage system that support different analysis algorithms. Different analysis tools have been implemented on the top the platform to perform iterative and incremental analysis through a dedicated web application. We plan to add new web components such as community analysis or heat map clustering representations, that can connect to the different data repositories in to build an observatory that can be used to perform explanatory analysis in real time.

## References

* Atzeni, Paolo / Bugiotti, Francesca / Rossi, Luca: "Uniform access to NoSQL systems". Information Systems, 43, 2014, pp. 117-133.

* Castrejon, J. / Vargas-Solar, G. / Collet, C. / Lozano, R.: "ExSchema: Discovering and Maintaining Schemas from Polyglot Persistence Applications", 29th IEEE International Conference on Software Maintenance (ICSM), 2013, pp. 496-499.

* Ghosh Debasish: "Multiparadigm Data Storage for Enterprise Applications", IEEE Software, 27(5), 2010, pp. 57-60.

* Hardebolle, Cécile / Boulanger, Frédéric: "Exploring Multi-Paradigm Modeling Techniques", Simulation, 85(11-12), 2009, pp. 688-708.

* Hodge, Bri-Mathias S. / Huang, Shisheng / Sirola, John D. / Pekny, Joseph F. / Reklaitis, Gintaras V.: "A multi-paradigm modeling framework for energy systems simulation and analysis", Computers & Chemical Engineering, 35(9), 2011, pp. 1725-1737.

* Moniruzzaman, ABM / Hossain, Syed Akhter: "NoSQL database: New era of databases for big data analytics-classification, characteristics and comparison", International Journal of Database Theory and Application, 6(4), 2013.

* Sharp, John / McMurtry, Douglas / Oakley, Andrew / Subramanian, Mani / Zhang, Hanzhong: "Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and Polyglot Persistence", In: Microsoft patterns & practices, 2013.

## Acknowledgements

The authors gratefully acknowledge Arnaud Da Costa, engineer in charge of the server infrastructure which was used during the TEE2014 project and Jonathan Norblin who developed the major parts of SNFreezer during the final internship of his masters degree in computer science.
## 2. Families of practices. A bottom-up approach to differentiate how French candidates made use of Twitter during the 2014 European Campaign

### Abstract

The aim of this chapter is to differentiate how French candidates made use of Twitter during the 2014 European campaign. We apply unsupervised learning techniques to let clusters of candidates emerge from the data. In particular, the variables used for clustering are operators interpreted by Twitter (hashtags, retweets, hyperlinks, mentions).

### 2.1 Introduction and rationale

The aim of this study is to understand how French candidates made use of Twitter during the 2014 European elections. In particular, we are interested in identifying a few families of practices, or “Twitter styles”, based on the operators found in the tweets. To this end we adopted a bottom-up approach, based on unsupervised learning (clustering). As a result we found three main “poles” defining the field of Twitter practices: some candidates tweet as a means for getting in direct contact with citizens, others diffuse hyperlinks to websites, while others still make an extensive use of the participative operators allowed by Twitter, such as hashtags, retweets and mentions. The results of this study permit to understand which practices are more common and to characterize them in accord to other variables such as the preferred tweeting interface of a candidate, his or her political party and the content of the words used in his or her tweets.

### 2.2 Corpus and methodology

The corpus used in this study was extracted from the TEE2014 database<fnref n="14" />. The database collects all the tweets produced by Belgian, English, French, German,

<footnote n="14">14 TEE2014 Project: http://msh-dijon.u-bourgogne.fr/recherche-msh/les-programmes/547-twitter-aux-elections-europeennes-une-etude-contrastive-internationale-des-utilisations-de-twitter-par-les-candidats-aux-elections-au-parlement-europeen-en-mai-2014-tee2014.html</footnote>
Italian and Spanish candidates to the European Elections 2014 during the campaign. Our corpus includes all messages tweeted by French candidates. In total, around 72.000 tweets by 467 users have been collected. We decided not to consider for our analysis 106 candidates who tweeted less than 15 tweets during the campaign, and 4 candidates who tweeted more than 1000 tweets, leaving a more homogeneous corpus of 357 candidates.

Data treatment, analysis and plots in this study have been realized with the open source statistical software *R* (R Core Team 2015), including the *dplyr* (Wickham / Francois 2015), *ggplot2* (Wickham 2009) and *cluster* (Maechler et al. 2015) packages<fnref n="15" />.

Our study focuses on candidates instead of on individual tweets. Therefore we began by summarizing for each candidate the proportion of tweets including an operator interpreted by Twitter (Thimm 2012, Einspänner / Dang-Anh / Thimm 2013). To calculate these proportions we have preferentially considered the meta-data present in the TEE2014 database, which in turn are based on the Twitter REST API (Twitter Inc. 2015) and on dedicated extraction algorithms. However we have recalculated these meta-data whenever needed by the ends of our research. The operators used in this analysis are the following:

1. The *retweet operator* “RT”: identifies retweets;

2. The *hashtag operator* “#”: identifies tweets containing hashtags;

3. The *hyperlink operator* “http”: identifies tweets containing links to webpages;

4. The direct message or reply operator “reply”, referred to as *DM/reply operator* from now on: identifies tweets starting with an “@” character;

5. The *source operator* “via”: identifies tweets ending with “via @” followed by a twitter account;

6. The *mention operator* “@”: identifies tweets including mentions in their text that are no retweet, DM/reply or source operator.

Other meta-data considered in the study are the candidate's *party name* and the *tweeting interface* most often used by him or her. The choice to focus just on operators to perform a clusterisation of the candidates in our corpus has been determined by past works on the TEE2014 database (Mercier / Villa 2015, Thimm / Einspänner / Gautier 2015) and by a previous exploratory research confirming the importance of operators as features to differentiate among the candidates' tweeting practices (Compagno 2015).

<footnote n="15">15 The script and the aggregated data are available for reproducibility by contacting the author.</footnote>
The aim of figure 1 is to show how many times each media logic operator has been used by French candidates. The ratio of tweets by a candidate that made use of a media logic operator is plotted on the x-axis of the facets: therefore a value of 0 means that a candidate never used a certain operator, a value of 1 that he or she used it in every tweet, and a value of 0.5 that we find that operator in every second tweet produced by the candidate. On the y-axis we find the number of candidates distributed according to the ratio of their tweets employing each of the six operators.

<figure><img src="image_13.png" /><figcaption>Figure 1. Use of media logics operator by candidates</figcaption></figure>

We can observe that the ratios of retweet and mention operators are centred and approximately normally distributed. The hashtag operator is slightly skewed to the left, suggesting that hashtags are often used in tweets. The hyperlink operator is instead more heavily skewed to the right, suggesting that there is a large number of tweets in our corpus not pointing to external webpages. This applies even more to the DM/reply and to the source operators: the vast majority of tweets are neither replies nor direct messages, and just a very small number of tweets in our corpus points to a source at the end of their text. However, we decided to isolate source operators, instead of considering them just as a kind of mention, because they correlate with the presence of hyperlinks in tweets, and would have acted as confounders in clusterisation.

Figure 2 permits to compare these different distributions more easily by plotting the median fraction of tweets per candidate that employ the operators. It is
evident that retweet, mention and hashtag operators are found approximately in every second tweet. Instead hyperlinks and especially DM/reply and source operators are much rarer and found respectively in one tweet of four, of fifteen and of one hundred.

<figure><img src="image_14.png" /><figcaption>Figure 2. Global use of media logics operators</figcaption></figure>

## 2.3 Exploration and clustering

In order to explore the relationships among the different operators, we performed a principal components analysis (PCA) using chi2 distances<fnref n="16" />, of which the results are shown on the left half of figure 3. PCA creates a space of representation in which observations (in this case candidates) can be positioned. The position of each point is determined by its preference to one or another operator. PCA therefore helps to understand if operators characterize mutually exclusive uses of Twitter. The first two factors of PCA, used as coordinates for our plot, explain respectively 40 % and 20 % of the point variability.

<footnote n="16">16 The function used to convert euclidean distances into chi2 ones has been developed at the *Laboratoire d'informatique théorique et appliquée* (LITA) de l'Université de Lorraine, that we would like to thank.</footnote>
<figure><img src="image_15.png" /><figcaption>Figure 3. *Principal components analysis*</figcaption></figure>
PCA shows that hyperlink and mention operators tend to be mutually exclusive: if a candidate makes a large use of the first, he or she will not often use the second, and vice versa. Source operators are positively correlated to hyperlinks: in fact, they are often automatically added to the end of the tweets produced by tweet buttons in news and other websites.

Hashtag and retweet operators tend to be used by the same family of candi-
dates. We can see that this third family does not make use of direct messages and
replies, nor publishes many links to webpages. Conversely, those who make heavy
use of DM/reply operators or of hyperlink operators do not insert many hashtag
or retweet operators in their tweets.

We begin to form an idea of the main trends in the use of Twitter by French candidates in the 2014 campaign: the majority of them, represented at the lower-left corner of figure 3, used hashtags and retweets but did neither tweet many hyperlinks nor engage in direct conversations. We notice two other tendencies: some candidates, at the lower-right side of the diagram, used Twitter mainly to diffuse hyperlinks, while some other candidates, at the top, got more involved in direct exchanges.

To get a better understanding of this insight we performed an agglomerative
hierarchical clustering on our data. This technique produces a segmentation of
the observations into a predetermined number of classes, according to the prefer-
ences that the candidates show about the use of operators. After exploring several
different partitions, we ended up with a five-classes clustering. The clusters are
plotted on the right half of figure 3, on PCA coordinates. We notice three “ex-
treme” groups of users and two intermediary ones.

The clusters are variable in size, as shown in figure 4. The largest, in the middle, that we called “Participative”, includes 164 candidates out of 357. The two small clusters at the extremes of the diagram, named “Interactional” and “Informative”, include respectively 6 and 33 candidates. The remaining two intermediary, medium-sized clusters named “Participative-Interactional” and “Participative-Informative” share what remains in two groups of 78 and 76 candidates each.

## 2.4 Interpretation of the clusters

Let us now enter into the details of the interpretation of these clusters. Figure 5
plots for each cluster the median fraction of tweets employing the media logic
operators. This profiling helps us to understand what the candidates in each
group have in common, and therefore to interpret these results. We chose not
to plot the source operator at this stage because it is not useful to differentiate
the five clusters.
<figure><img src="image_16.png" /><figcaption>Figure 5. Profiling of the Twitter Styles</figcaption></figure>

<figure><img src="image_17.png" /></figure>
We named the first cluster on the left “Interactional” because the candidates in it used Twitter mainly to engage into direct conversations with other users. More than the 70 % of tweets produced by the candidates in this group are direct messages or replies. On the contrary, hashtag, hyperlink and retweet operators were very rarely used. Mention operators are found in one tweet of four. This tweeting style is highly unconventional, exploiting to the largest extent one minor function of Twitter (that of sending messages addressed to individual users). And in fact only a very small number of candidates, six, used Twitter in this manner. With some irony, we could say that tweets are seen by the users of this group as a substitute for SMS.

Moving to the other extreme of the diagram, to the farthest right, we find the “Informative” group. These candidates used Twitter almost exclusively as a means to diffuse information produced elsewhere, in the form of hyperlinks. They made a very modest if any use of all other operators. With another metaphor, we could say that Twitter is seen by this group’s members as a kind of RSS publisher and reader: they post links to websites but do not make use of other operators specific to Twitter. This cluster is the second smallest, including 33 candidates, and represents a second “deviant” use of Twitter – opposite to the first interactional one. Both these tweeting styles constitute radical exceptions to the most common use of Twitter, and they play an important role in shaping the spectrum of alternative uses allowed by this social medium.

At the centre of the diagram we find the largest cluster. The candidates in it made heavy use of hashtag, retweet and mention operators. We named this cluster “Participative” because these operators are meant to promote participation in larger exchanges and discourses: hashtags are anchors to certain events or topics, retweets are instruments of Twitter’s polyphony, repeating what was said by others, and mentions invite specific users (and their followers) as interlocutors. Participative candidates rarely engage in direct conversations and do not publish many links to external resources. They play with the operators most specific to Twitter: retweets, hashtags and mentions were born on this social medium and appear to define its most common use. We could say that these candidates practice “pure tweeting”, with no immediate interactional nor informative ends.

The “Participative_Interactional” cluster is an intermediary between pure interaction and pure participation. A fifth of the tweets produced by the users in this group were direct messages or replies, which is thrice as much as the global median. In addition to this, hashtag, retweet and mention operators are found each in 40 to 50 percent of their tweets. These candidates participate to the “meaning game” proper to Twitter, but also interact individually with other users.
The last remaining group, “Participative_Informative”, is also an intermedi-
ary one. One of two tweets produced by the members of this cluster contains a
hyperlink. Hashtag and retweet operators are found with the same frequency.
Mentions are used slightly less, around a third of the times. Candidates in this
cluster use hyperlinks twice as often as the global median, and also participate
with hashtags, retweets and mentions.

## 2.5 Structuring the Tweeting practices of French candidates

These considerations could be thought as a way to give a structural description
of the norms regulating the use of Twitter by French candidates during the 2014
campaign. The statistical tools make some of the semiotic norms visible, allow-
ing the researcher to access new aspects of this practice. Rastier (2011) refers to
the discourse norms made visible by corpus analysis as “new observables”. In our
case, the clusters built on the use of the operators help to define the norms active
in this field of tweeting practices.

The five families of tweeting practices are organized around *three poles*: the *participative*, the *informative* and the *interactional*. The three “pure” clusters are each close to one pole and far from the other two, while the two intermediary clusters are each close to two poles and far from the remaining third. It should be noticed that no candidates adopted a style close to the informative and to the interactional poles while being far from the participative one. It means that, in our corpus, informative and interactional uses of Twitter are mutually exclusive (there is no “Interactional-Informative” style).

This configuration allows us to talk about *two opposite tendencies*: an interac-
tional and an informative one. When referring to a tendency, we will talk about
both pure and intermediary clusters (for example, both the informative and the
participative-informative clusters constitute the informative tendency). Schema 1
resumes the configuration of poles and tendencies.

It should be noticed that even if Twitter could have been used by candidates at
the same time as a means to send personalized messages (to interact) and mes-
sages with a broader reach (to inform), no candidate used it in this way. Also, the
diffusion of hyperlinks is very rarely accompanied by personalized mentions,
excluding from the observed field of practices the possibility of a “hybrid” between
interaction and information. Twitter was not an instrument to send personalized
links to websites.
<figure><img src="image_18.png" /><figcaption>Schema 1. Poles and tendencies</figcaption></figure>

Candidates preferred either a more personalized approach or a more impersonal one, therefore showing that they conceptualized the medium in two very different ways, exploiting different aspects of its potential. It would be interesting, in future research, to further explore the structure of different fields of practices, and compare them. This could result in a better understanding of how technical potentials are reduced to a smaller set whenever their use is filtered by social and semiotic norms. The patterns of this reduction would point to some of the logics of culture and communication, regulating human exchanges.

Twitter *per se*, as a technology, allows a number of different uses: with Eco (1979) we could say that the Twitter *model user* is broadly defined, permitting many potential uses to co-exist. However what matters the most in this case is the transition between the model user and the *empirical uses*: the individual uses of the social medium. What characterize this transition are the norms, made visible in our diagrams, that cause just a limited number of families of uses to actually exist. If it is true that every candidate behaves differently, and if it is also true that
Twitter gives the same potential to all candidates, we still manage to identify a few main patterns. Therefore it is exactly *in the constitution of these patterns* that we may see the effect of the social and semiotic norms responsible for reducing the large virtual potential of Twitter to a small number of actual families of uses.

French political communication showed difficulties merging two tendencies: the informative and the interactional. Maybe French candidates consciously perceive these two tendencies as mutually exclusive, and believe that a hybridization would be seen as contradictory by citizens. Another hypothesis could be that merging information and interaction, for example by sending to individual users many personalized references to websites, would simply be a costly activity.

## 2.6 Associations between clusters and tweeting interfaces

The five clusters have been calculated exclusively on the recurrence of operators in the candidates' tweets. Therefore, we may now look for further associations between those families of practices and the other variables at our disposal. This may help us to better understand the tweeting styles and also to characterize the other variables' levels on the base of what we have discovered.

We are going to start by observing how the clusters are associated with the preferred tweeting device of each candidate. This is important because different interfaces may produce different experiences of the medium, exposing users to subsets of the Twitter flux or making the use of some operators easier. Figure 6 plots the number of candidates using each tweeting interface most often. The colours of the bars indicate to which tweeting style the candidates belong.

We notice immediately that one interface (Twitter for iPhone) is more frequently used than all other ones (by 154 candidates in 357). The second most popular one (the Twitter website accessed with a web browser) is used by 71 candidates. Twitter for Android is used preferentially by 50 candidates, making it the third most popular. We find three other interfaces preferred each by 8 to 17 candidates (Facebook, Twitter for iPad, tweet buttons embedded in websites) and a higher number of interfaces used each by less than 8 candidates (summing up to 41 candidates and represented as the column "Other" in the diagram).
<figure><img src="image_19.png" /><figcaption>Figure 6. Interfaces preferentially used for twitting</figcaption></figure>

The three major interfaces are used by candidates in all clusters. However, we see that the proportions vary. The candidates using Twitter with an app for smartphones or tablets (either on iOS or on Android) tend to be more participative, and use Twitter to inform as much as to interact with other users. Candidates using iPads in particular use Twitter only rarely to distribute hyperlinks. Instead, the candidates tweeting from a web browser tend to be more informative than participative: as many of them are found in the informative cluster as the sum of those found in the participative and interactional ones.

This tendency becomes predominant for users tweeting from a Facebook application or from tweet buttons found directly on websites: almost the totality of these candidates use Twitter prevalently to distribute hyperlinks. In particular, a small subset of 7 candidates in the informative cluster makes a noticeable use of the source operator (in one tweet of three). This subset mostly uses tweet buttons to tweet, rather than Facebook or other interfaces. Finally, candidates using prevalently other interfaces seem to make the most balanced use of Twitter, as the distribution of clusters in this group closely resembles the global one.

Do the interfaces facilitate a certain approach to the medium, or is there another explanation for the association between the candidates' tweeting styles and their preferences for a certain interface? Candidates using tweet buttons and Facebook application to tweet may actually not fully master the operators specific to Twitter (hashtags, mentions) and therefore adopt an informative
tweeting style just because they tweet as a “residual” secondary activity, in which they are not that confident or competent. On the other hand, iPhones and other mobile devices do allow a continuous scan of the Twitter flux, and so they may invite the user to retweet more often, or help to internalize the use of hashtags. Our study points to some potential paths that should be verified, either with experimental procedures, or with the analysis of dedicated datasets, accompanied by a semiotic comparison of the tweeting interfaces (Zinna 2004).

## 2.7 Associations between clusters and political parties

The families of Twitter practices that we have identified are not homogeneously distributed among the political parties of the candidates. Figure 7 shows the number of candidates for each of the major parties (with at least 15 tweeting candidates in our corpus), and the colour of the bars identifies the family to which the candidates belong.

<figure><img src="image_20.png" /><figcaption>Figure 7. Distribution of clusters among parties</figcaption></figure>

Two of the largest parties, PS-PRG (“Parti socialiste – Parti radical de gauche”) and UDI-MODEM (“Union des démocrates et indépendants – Mouvement démocrate”), show a similar distribution. Around 75 % of their candidates belong to the participative cluster, and the remaining ones are equally divided between the informative and the interactional tendencies. The candidates of the UMP (“Union
pour un mouvement populaire”) party are more attracted by the interactional pole: around 62 % of them adopted a participative style, while 31 % were more interactional and 7 % more informative. The fourth largest party, EELV (“Europe écologie les verts”), was instead more attracted by the informative pole (51 % participative, 31 % informative tendency, 17 % interactional tendency).

Among the four smaller parties, the Parti Pirate shows the most pronounce bias towards the interactional pole, with around the 75 % of its candidates tending towards it; just one in fifteen candidates has been classified as purely participative and the other three show an informative tendency. The FDG (“Front de gauche”) shows the opposite configuration, with 50 % of participative candidates and 41 % of informative ones. The candidates of the FN (“Front national”) were more informative (48 %) and almost equally participative and interactional (28 % and 24 % respectively). Last, Nous Citoyens was mainly participative (43 %), and more interactional (35 %) than informative (22 %). Figure 8 resumes this information with a PCA plot.

<figure><img src="image_21.png" /><figcaption>Figure 8. Principal components analysis (parties and tendencies)</figcaption></figure>

We can observe that the Parti Pirate is the most interactional, while the FN and the FDG are the most informative, and the PS-PRG and UDI-MODEM the most participative. The UMP is equally interactional and participative. It is not possible to associate a certain tweeting tendency to the leftist or rightist orientation
of a candidate. We remark that the most extremist parties (FN, FDG) adopt more informative styles, while the moderate ones (PS-PRG, UDI-MODEM, UMP) tend to be more participative. However it should be noticed that the moderate parties are also the largest ones.

## 2.8 Classification of tweets based on textual analysis

In the last step, we wanted to know if our clusters could be further characterized on the basis of the discourses realized by the candidates in their tweets. Thanks to the software Iramuteq (Ratinaud 2009), we performed to this end a classification of the tweets' texts, based on the co-occurrence of words (Reinert 1983). As a result of this classification, the tweets in our corpus have been preferentially related to one of two ample classes of co-occurring words. Similitude diagrams for the two classes, realized with Iramuteq, are shown in figure 9.

The left half of the figure describes the first of the two classes, that we have called “Political Issues”. The words in this class are mainly related to political topics, such as the relationship between France and the European Union, the conduct of the French prime minister François Hollande, the relationships between the three main French parties PS, UMP and FN. Economic issues were also mentioned during the campaign and are included in this class, such as the TAFTA, unemployment and growth. The right half of figure 9 instead describes the lexical class we called “Electoral discourse”. It includes hashtags and words used during the campaign to communicate about events, meetings, debates and the elections dates. The two lexical classes are intentionally broad, but give some hints about the contents most addressed by the different parties on Twitter.

Based on the classification of the tweets realized with Iramuteq, we calculated the preference of each candidate's tweets for political issues or for the campaign itself. Figure 10 plots the preferences of the candidates in each cluster.
<figure><img src="image_22.png" /><figcaption>Figure 9. Lexical classes of the Tweets' texts</figcaption></figure>
<figure><img src="image_23.png" /><figcaption>Figure 10. Preference to lexical classes among clusters</figcaption></figure>

We notice that in the participative cluster political issues and the electoral dis-
course appear to have the same importance. All the other clusters instead show
a preference for the political issues, and this preference is more pronounced on
the interactional side than on the informative side. Some of the tweets have not
been categorized (they are coloured in green in figure 10), because in most cases
they only included a hyperlink without any commentary. The majority of the
candidates most often using uncategorised tweets belongs to the purely informa-
tive cluster. Figure 11 plots the preferences of each of the major political parties
for political issues or for the electoral discourse.

The Parti Pirate is the one most focusing on political issues, followed closely
by the EELV. On the opposite, 65 % of the UMP candidates mostly focused on
the electoral discourse, followed by the UDI-MODEM (55 % of the candidates).
This information should be complemented by the associations between clusters
and political parties seen above: the Parti Pirate and the UMP were the most
interactional parties; however, it seems that the kind of interaction they perform
differs between the two. Our research appears to show that the members of the
Parti Pirate use Twitter prevalently to engage in one-to-one conversations about
political issues (a *personalized political debate*), while those of the UMP use Twitter
to realize a *personalized electoral discourse*, inviting individual users to meetings
and other occasions. In these two cases, we can talk of sub-styles of tweeting, de-
fined within the interactional tendency. Textual analysis could be exploited even further to identify more tweeting sub-styles.

<figure><img src="image_24.png" /><figcaption>Figure 11. Preference to lexical classes among parties</figcaption></figure>

## 2.9 Conclusion

We have found tendencies in our corpus that show how semiotic and social norms reduce and channel the technical potentials of a social medium. Twitter gives space to many different individual uses, but just a few families of uses, or “tweeting styles”, are actually realized. These styles are not homogeneously distributed among the political parties of the candidates. We have also found further associations between the tweeting styles and some other variables, such as the kind of discourse realized in the tweets’ texts or the favoured tweeting interface.

The next step of our research will be to perform a similar analysis to other corpora extracted from the TEE2014 database. We want to know if Belgian, English, German, Italian and Spanish candidates use Twitter in a comparable way to the French. Some of the tweeting styles we found in France may not exist elsewhere, or their importance may vary from one country to another. After having extended our research to a larger corpus we may be able to produce a better structural description of the norms guiding the use of Twitter for electoral communication in Europe today.
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3. Exploring the dialogical dimension
of political tweets: A qualitative analysis
of ‘Twitter styles’ of UK candidates during
the 2014 EU Parliamentary Elections

Abstract

This chapter looks more closely at « informational » and « interactive » communication
styles on Twitter, qualitatively examining the multiple and contrasting ways in which dif-
ferent functional operators can be used, and proposing a model based on the “dialogical
potential” of the tweet, which aims to avoid some of the more reductive generalisations
commonly found.

**3.1 Introduction**

Since Twitter has become widely used by politicians in many countries, much
has been written about the different ways in which this tool is, can and should be
exploited (Frame and Brachotte 2015; Jackson and Lilleker 2011; Larsson and Moe
2013; Parmelee and Bichard 2013). Many researchers have denounced a general
tendency for politicians to try to reproduce one-to-many communication strate-
gies, tweeting *at* their voters rather than seeking to ‘interact’ with them in what
is often presented as a more appropriate ‘web 2.0’ style (Small 2010; Vergeer and
Hermans 2013). Further attempts have been made to classify communication
styles on Twitter, generally ranging between the two poles of one-to-one (inter-
active) and one-to-many (informational) (Dang-Anh, Einspänner, and Thimm
2012; Eyries and Poirier 2013; Sæbø 2011). This chapter will build on existing
approaches to study to what degree the use of different operators on Twitter ap-
pears to be correlated with different “Twitter Styles” (Dang-Anh, Einspänner,
and Thimm 2012). Adopting a qualitative, context-based approach to analyse
messages sent by UK candidates at the European Parliamentary Elections in May
2014, we will seek to further characterise the uses and perceived communica-
tive functions of the Twitter-specific communication operators (@, RT, #, http)
which contribute to making the micro-blogging network a specific discursive
space (Dang-Anh, Einspänner, and Thimm 2012). Anne-Marie Paveau argues
that Twitter discourse, as a specific ‘techno-discursive’ production can be seen to
constitute a new genre: “Twitter writing” (Paveau 2012), while Michele Zappavigna sees the discursive dimension of the platform as the key to understanding its “networks of affiliation” (Zappavigna 2012).

Interactions between users on Twitter are the bricks and mortar of the web-based community, the Twittersphere, which, from a technical if not a social point of view, has high potential for generating exchanges in political communication (Ausserhofer and Maireder 2013; Thimm, Einspänner, and Dang-Anh 2012a). When studying online interactions or computer-mediated communication (CMC) it is important to take into consideration interpersonal social interactions (Goffman 1967) but also the specifics of the medium, the technical devices used and their functions (Coutant and Stenger 2010). Compared to face-to-face interactions, the absence of non-verbal means of communication like gestures, mimics, intonation etc. should be taken into account, as well as potential erasing of social distance between communicants, time and place indeterminacy (Bucher 2004). At the same time, the construction of a dialogical situation could be compared to offline communication in terms of the background social and cultural knowledge required to produce and interpret symbolic acts. Language skills and knowledge about the structure and functions of the mediating technical devices are necessary to “release the interactive potential” of the interface (ibid.).

In our approach, we do not limit interactions to face to face exchanges (Goffman 1967), but extend this notion to all human activities in which two or more actors are involved (Vion 1992), at least potentially. Publishing tweets in the Twittersphere involves one<fnref n="17" /> or more actors, and may create a constellation of “interactants” (Charadeau and Mainqueneau 2002), if we take into account the potential audience of the message posted, or indeed the ‘conversations’ it generates. The ‘presence’ of face-to-face interactions is recreated in CMC by various means by which the device allows users to organise their discourse (Bays 1998). Non-verbal interactions are compensated for by other elements inherent to the device’s technical structure: in the case of Twitter, these are the communication operators. As Caja Thimm and colleagues have pointed out, each sign becomes a communication operator by taking on different functions within the context of the Twittersphere, as characterized here:

<footnote n="17">17 The use of the term “interaction” to describe a tweet sent by one person may seem inappropriate. However, we consider it justified by the idea that the person composing the tweet has in mind a potential audience: it is a social act in Goffman’s sense, obeying Bakhtinian principles of dialogism (*infra*).</footnote>
<figure><img src="image_25.png" /><figcaption>Figure 3.1 Classification of communication operators (Thimm, Einspänner, and Dang-Anh 2013)</figcaption></figure>

Based on their analysis, Thimm and colleagues distinguish two major “Twitter styles”: the interactive-personal style, characterised by tweets which invite interactions and interpersonal exchanges, and the thematic-informative style, more concerned with distributing information (Thimm, Einspänner, and Dang-Anh 2012b). The former is characterized by an abundant use of @ and RT operators, while the latter favours external links. In order to simultaneously question and further characterise these styles, this chapter focuses not only on the communication operators, but on their functions as deployed in a specific tweet which can be interpreted in its technical and communication environment and in relation to a wider social and political context. We can ask, for example, whether a journalist who systematically adds to her professional tweets the Twitter handle of the newspaper for which she works, @Telegraph, should accurately be described “interactive”: she is most probably not seeking a reaction from the newspaper but looking to give her tweets more visibility while underlining her professional affiliation. Similarly, if someone tweets a link in order to provoke reactions from friends, are they employing a solely “informational” strategy? This chapter will endeavour to propose a heuristic framework allowing us to better take into account such specificities.

## 3.2 Twitter styles revisited

In order to further characterize the Twitter styles, by building on various approaches and trying to limit the overall number, we can list a certain number of
partially overlapping major communication functions: addressing, mentions or referencing, contextualisation, argumentation, and passing on information. These can then be related to the communication operators, as presented in Figure 2: each communication operator possesses a main function but could partially fulfill the adjacent functions as well.

<figure><img src="image_26.png" /><figcaption>Figure 3.2 Five major communication functions correlated with operators</figcaption></figure>

A slightly different way of thinking about the interaction/information continuum is to consider the potential reach of a tweet. A tweet's reach is defined as the number of accounts to which it is potentially visible. A tweet sent by an account (x) becomes potentially visible to another (y) when any of the following conditions are fulfilled:

(a) the account owner of y follows account x;

(b) the tweet sent by x contains the name of account y (an "@ mention");

(c) an account followed by y retweets the tweet sent by x;

(d) the tweet sent by x contains a # which y searches for (or follows using a specific tool);

Some tweets, for example addressed by one account with relatively few followers to another, may have very low reach, potentially being seen by only a few other users. On the other hand, a tweet including very popular twitter handles, plus common or trending hashtags can potentially be seen by millions. Although a lot depends on the actual contents and context of the tweet itself, the functions
previously listed can be roughly correlated with their potential reach or the vis-
ibility they may give to a particular tweet, as resumed in Figure 3:

<figure><img src="image_27.png" /><figcaption>Figure 3.3 Relative potential reach of major communication functions</figcaption></figure>

In other words, depending on a communication operator and its contextual func-
tion, as well as the element with which the operator is directly combined, its
neighbouring elements and their occurrences and significations in a wider con-
text, we can consider that a tweet will have greater or lesser potential reach. It is
the technical nature of the operators and the way they function in this particular
medium, in relation with the communication environment, that allows us to talk
of a ‘techno-discursive platform’, where the technical elements mobilised in a
given interaction contribute to produce pre-programmed dialogical configura-
tions. Their previously-accumulated knowledge about how these technical ele-
ments function will allow Twitter users to employ them to seek to achieve certain
functions and effects within the Twittersphere. This is close to the dialogical situa-
tions encountered in offline communication where participants seek to anticipate
potential acts and utterances from their partners, and indeed this conscious or
unconscious intersubjective anticipation takes place alongside more technical
calculations within the Twittersphere too. Whether the partner is fictive or vir-
tual, the way discourse is constructed is guided by principles of dialogue. From a
Bakhtinian perspective (Бахтин 1996), dialogism is a characteristic phenomenon
of all speech, even in the case of a monologue.

Indeed, political tweets correspond completely to Bakhtin's logic: the meaning
attributed to any tweet is linked to the accumulated tweets of the Twittersphere,
and politicians try to take into consideration their potential audience(s). By look-
ing at the way tweets are constructed, we can reason in terms of Bakhtin's logic of
the double dialogical extension of discourse (Бахтин 1996). This concept has been
used to analyse political discourse online (Bonhomme and Stalder 2006), and
allows us to bring together all of the elements that favour a (supposed) dialogue
online: producer, potential receiver, different codes of communication (e.g. @, #
in case of Twitter), other discourses. Figure 3 (*supra*) can be used to illustrate the
different degrees of dialogism which can potentially be associated with different
communication functions, and to underline the applicability of this concept to
the Twittersphere. In our analysis we will use it in order to evoke the degree of
involvement of a Twitter user in a potential dialogue through a tweet. Following
on from this discussion, we can formulate two hypotheses:

1. "Twitter styles" are not determined only by the prevailing number of com-
munication operators in a tweet but especially by the correlations of operators'
functions as actualized in discourse (the tweet and its wider context).

2. Based on the concept of the dialogism applied to Twitter (Figure 3), we hypothesise that the more determined a potential receiver is (low reach), the higher the degree of implication in a dialogue (dominantly interactive tweet) and, conversely, that the larger the potential audience (high reach), the less the dialogical function is actualized in a tweet (dominantly informational tweet).

These hypotheses were tested by applying them to the corpus of tweets sent by
UK candidates during the European Parliamentary Elections, collected within
the framework of the TEE2014 project.

**3.3 Methodology & results**

The corpus consists of all of the tweets of the 309 Twitter accounts which were
identified as belonging to UK candidates for the European Parliamentary elec-
tions on 22nd May 2014, sent in the three-week run-up to the Elections and in
the week following the vote (1st May to 27th May). 72 860 tweets were collected
overall. From this corpus, we selected all candidates who had produced more than
50 tweets during the period, this being considered a minimum number for us to
be able to usefully characterise the Twitter styles of a particular candidate. This
query resulted in a list of 213 candidates. The final step was to reduce this list to
a smaller number of candidates enabling us to carry out qualitative analysis to
gain insights into the way particular operators and functions were being used.
In order to obtain a varied selection of accounts, we chose to take the two candi-
dates whose tweets had the highest percentage of each communication operator,
the two candidates with the lowest percentage and two balanced accounts which
seem to have close to average numbers of each communication operator (n=18 accounts).<fnref n="18" /> The profiles of these accounts are as follows

1. Abundance of communication operators: highest percentage<fnref n="19" /> of media<fnref n="20" />, RT, http, hashtags and @ (8 accounts).

2. Balanced accounts where the number of each communication operator varies between 25 and 60 percent (2 accounts).

3. Lowest percentage of communication operators (8 accounts).

The first fifty tweets collected for each account were analysed (n=900 tweets). The accounts selected are presented in Table 1, along with the number of communication operators used by each candidate, and the percentage of tweets in which each communication operator was used:

<table><caption>Table 3.1: General information about candidates and statistics about communication operators used</caption><thead><tr><th>Twitter_handle</th><th>local_list_name</th><th>place_on_list</th><th>Total_tweets</th><th>Total_RT</th><th>RT %</th><th>Total_url</th><th>url %</th><th>Total_#</th><th># %</th><th>Total_at_at %</th></tr></thead><tbody><tr><td>@LindaMcAvanMEP</td><td>Labour</td><td>1</td><td>53</td><td>32</td><td>60</td><td>4</td><td>7</td><td>28</td><td>52</td><td>34</td></tr><tr><td>@SimonDarbyGB</td><td>British National Party</td><td>5</td><td>54</td><td>1</td><td>1</td><td>53</td><td>98</td><td>0</td><td>0</td><td>1</td></tr><tr><td>@EnzaFerreri</td><td>Liberty GB</td><td>2</td><td>58</td><td>2</td><td>3</td><td>56</td><td>96</td><td>0</td><td>0</td><td>1</td></tr><tr><td>@OlwenHamer</td><td>Labour</td><td>5</td><td>61</td><td>52</td><td>85</td><td>1</td><td>1</td><td>22</td><td>36</td><td>49</td></tr><tr><td>@JonathanArnott</td><td>UKIP</td><td>1</td><td>64</td><td>0</td><td>0</td><td>32</td><td>50</td><td>13</td><td>20</td><td>16</td></tr><tr><td>@DianeDoddsMEP</td><td>Democratic Unionist</td><td>1</td><td>67</td><td>24</td><td>35</td><td>3</td><td>4</td><td>19</td><td>28</td><td>27</td></tr><tr><td>@cpasoutheast</td><td>Christian Peoples Alliance</td><td>1</td><td>80</td><td>1</td><td>1</td><td>67</td><td>83</td><td>1</td><td>1</td><td>0</td></tr><tr><td>@yes_edin_south</td><td>Scottish National Party</td><td>3</td><td>116</td><td>69</td><td>59</td><td>33</td><td>28</td><td>53</td><td>45</td><td>66</td></tr><tr><td>@hudghtonmepSNP</td><td>Scottish National Party</td><td>1</td><td>130</td><td>120</td><td>92</td><td>21</td><td>16</td><td>103</td><td>79</td><td>86</td></tr><tr><td>@ansar_ali_khan</td><td>Labour</td><td>4</td><td>140</td><td>114</td><td>81</td><td>4</td><td>2</td><td>44</td><td>31</td><td>126</td></tr><tr><td>@jayne_shotton</td><td>Labour</td><td>3</td><td>145</td><td>68</td><td>46</td><td>56</td><td>38</td><td>44</td><td>30</td><td>66</td></tr><tr><td>@KSillsEngDem</td><td>English Democrats</td><td>1</td><td>163</td><td>1</td><td>0</td><td>155</td><td>95</td><td>2</td><td>1</td><td>16</td></tr><tr><td>@jackbuckby</td><td>Liberty GB</td><td>3</td><td>246</td><td>6</td><td>2</td><td>24</td><td>9</td><td>1</td><td>0</td><td>147</td></tr><tr><td>@kev927riddy</td><td>English Democrats</td><td>1</td><td>322</td><td>5</td><td>1</td><td>297</td><td>92</td><td>2</td><td>0</td><td>19</td></tr><tr><td>@maryhoneyball</td><td>Labour</td><td>2</td><td>342</td><td>208</td><td>60</td><td>29</td><td>8</td><td>102</td><td>29</td><td>319</td></tr><tr><td>@JillEvansMEP</td><td>Plaid Cymru</td><td>1</td><td>388</td><td>349</td><td>89</td><td>86</td><td>22</td><td>196</td><td>50</td><td>333</td></tr><tr><td>@DavidoOrr</td><td>British National Party</td><td>2</td><td>397</td><td>200</td><td>50</td><td>10</td><td>2</td><td>317</td><td>79</td><td>80</td></tr><tr><td>@guydessoy</td><td>Animal Welfare</td><td>7</td><td>447</td><td>110</td><td>24</td><td>152</td><td>34</td><td>368</td><td>82</td><td>126</td></tr></tbody></table>

The candidates are classified by number of total tweets produced during the period of analysis. The selection criteria resulted in a fairly even spread of parties

<footnote n="18">18 Where several candidates had the same score for a particular communication operator, the first one in the list of results was selected.</footnote>

<footnote n="19">19 The percentage is calculated in relation to the total number of tweets produced by a candidate during the period of analysis.</footnote>

<footnote n="20">20 By “media” we understand all photos & videos that were used by a candidate in her/his tweet.</footnote>
and constituencies being retained, although candidates close to the top of their
particular list appear to be overrepresented. It should be highlighted that in some
cases (@LindaMcAvanMEP) the abundance of one communication operator is
associated with high use of another (high rate of RT and @, > 60 %), while in
other cases (@KSillsEngDem) there is a considerable preponderance of one type
of communication operator (almost) exclusively. Several accounts fulfilled sev-
eral criteria at the same time, for example that of @EnzaFerreri had the highest
percentage of http, as well as the lowest of # and @.

Discourse analysis of the 900 selected tweets was carried out in the following
steps:

1. A communication operator (@, #, httpor RT) was selected.

2. On the basis of the influence of neighbouring elements on the communication operators' function, operators were manually coded using Nvivo, depending on their accompanying element; For example, @Telegraph = @+name_of_media_source.

3. The whole syntagm was analysed, including the neighbouring elements such as prepositions, names of other people, adverbs or other communication operators that could define, change or complete the first function.

Once coded, the tweets, the communication operators and their functions were
analysed manually, while Nvivo was used to give insights into word frequency.

**3.4 Results and Analysis**

**3.4.1 The operator @**

We began by seeking to establish the degree to which the operator @ can be seen
as marker of an “interactive style”. A first set of tweets were coded as @+name
of a personal account. It should be noted that some accounts, such as @Skoosh-
bag, are less transparently personal accounts than others which simply prefix the
@ operator to the first name and surname. Most of the time, the account profile
description allowed us to clarify this. These tweets often seem to show @ in its
primordial function of addressing:

(1) @meljomur @votingyes @Skooshbag @Celebs4indy I wasn't there unfortunately but this post covers general feedback https://t.co/kfuXp Yzihz<fnref n="21" />

<footnote n="21">21 Because of the way in which the data was collected, it was unfortunately not possible to reproduce screenshots of all tweets showing them in their original context. For this reason, only the text of the tweets is reproduced here.</footnote>
(2) @votingyes @Skooshbag @meljomur @DRossborough @Celebs4indy all the more reason to take the positive case to these areas.

(3) @roselearran me too!

The first tweet has a neighbouring element http(1) to introduce a supportive argument, the second (2) and third (3) ones obviously have a responsive character. The second tweet illustrates various types of accounts associated with an @ operator, with different degrees of dialogical potential depending on the nature and character of the account: @votingyes = @+name of community, @Skooshbag= @+name of a personal account. From a political communication perspective, this type of @ also includes politicians' personal accounts: @+name of a politician, as in (4) and (5).

(4) RT @CllrAlexander: Great turnout for Dundee... http://t.co/mCDQXhK0I8

(5) @CllrAlexander this for talks as a rally or a big work session?

In the fourth case @ is arguably not a simple marker of interactivity any more (4), since its function has been changed through the presence of another communication operator RT. The goal of this retweet would appear to be referential rather than to enter into a dialogue, though in practice, since the original account is automatically notified of any retweets, this can also be considered as a particular form of dialogical interaction. The counter-example of a tweet using the same operator @+name of a politician (5) but accompanied by a question and not a RT radically changes its character and it can much more easily be seen as a part of a dialogue.

It is interesting to note that there are several cases of non-use of the operator @+name of a personal account, where opponents refer to the name of the opposite party's member without using the corresponding Twitter handle (6). In contrast to this tendency, political allies are more likely to be introduced directly with @, for instance (7), addressing or referencing a fellow member of Scottish National Party.

(6) SoFarage thinks all Romanians are people smugglers & Tory MEP cand Ian Duncan thinks Scots Chinese all eat cat. Fundamentally flawed people

(7) @ToniGiugliano on why we must be independent in Europe: http://t.co/kx20mtbNji#ep2014 http://t.co/MQoTPwpNTi.

It is unclear whether the use or non-use of a communication operator here is premeditated or just fortuitous, as counter-examples exist, yet it would appear to make sense as a political strategy designed both to expose one's own message to a sympathetic public which does not necessarily follow one's own account, or indeed to avoid a hostile audience in the case of non-use of an opponent's Twitter
handle. It could also be seen as a way to draw attention to an ally's account, but not to that of a political opponent.

The operator @ was very frequently used in its so-called "gratification function" when accompanied by a neighbouring element such as "thanks" (8) (9) or in its localising position accompanied by a preposition of localisation "with" (10).

(8) @AmranHussain @LondonLabour @ClaudeMoraesMEP @Lucy4MEP @SebDance
Very many thanks Amran!

(9) @DaveCharnley1 @AnneFairweather @ClaudeMoraesMEP @Lucy4MEP v many thanks Dave

(10) Campaigning with @BarnetLabour & going to Hale ward with @sebdance @giam-pialhadeff

The construction **@+name of a personal account** + thanks, with, etc. could not be considered as completely non-interactive, because the person in question is addressed (8) (9) or at least mentioned (10), nevertheless its dialogical potential would appear to be relatively lower than in cases of questions or answers (3).

It should be highlighted that constructions of the type **@+name of a tweeting candidate** retweeted by the candidate him/herself are widespread in the political Twittersphere.

(11) RT @redstarneil: Thank u @maryhoneyball et al 4 supporting @QPLabour today.
Look forward 2 working with more of you! #labourdoorstep http://...

The degree of the implication in a dialogue appears here to be low (11). The function of this communication operator, in relation with its neighbouring elements, seems to aim more at gaining visibility rather than interaction. In a similar function we find another type of @: **@+party name**.

(12) Did Labour and the Conservatives do well for the North East 2006-2012? Don't vote for more of the same, vote @UKIP. http://t.co/s6o28eJgk8

In the example (12) the dialogical potential appears seriously limited, and the tweet seems to aim rather at increasing the visibility of the party in question by mentioning it, or indeed at attracting new followers to the author's own account by showing party affiliation. This is an example of a more general strategy which can often be observed.

The last category of @ that we would like to emphasise in this study is **@+name of media source** that seems to reveal the polysemic potential of this communication operator's functions.

(14) Great start for Louise Bours on Question @bbcquestiontime!

(15) @itvnews There's a revolution happening. Many Londoners are planning to #Vote-AnimalWelfareParty this Thursday EU elections. Are u following?
(16) “@TheEconomist: Losing America cost King George III his sanity. Mr Cameron thinks losing Scotland would not even cost him his job” losing??

This type of @ usage often appears more informative than interactive. It can be
used for argumentation purposes (15) (16) or for passing on information (14).

Through examples 1–16, the @ operator can be seen to potentially fulfil various functions, with different degrees of implication in dialogue. This depends notably on the neighbouring elements that introduce this operator, and the nature of the account with which it is associated: name of a personal account, name of political party or organisation, or name of media.

3.4.2 The operator RT

This communication operator is by nature heteroglossic in Bakhtin's sense, it
refers to the words of others, and can be used to pass on information, sometimes
accompanied by argumentation. Once again, its exact nature and function are
strictly dependant on its context of usage.

In the cases where RT introduces a tweet from a personal account (1), it fulfils
its referencing function as a mention that possesses some dialogical potential, and
may imply a community of interactants.

(1) RT @tobyperkinsmp: Great to join @WMLabour Euro candidate @ansar_ali_khan & Sir Albert Bore to see Labour investment on Metro extension ht...

Retweeted tweets may also themselves be retweeted (2), possibly with additional comments or reactions, creating a chain of interactions and presenting an interesting case of an enlarged discursive sphere.

(2) RT @ChorltonGreen: RT @ranty_man: Hunt is desperately trying not to alienate former Labour voters #BBCQT; is it working?

Other examples show that when RT introduces the parties' speech (3) (4) (5), it appears to lose much of the dialogical potential of the examples above (1) (2). The goal of such retweets is generally to pass on information, assure parties' visibility or associate oneself with the particular point of view, event, etc. contained in the original tweet. This kind of tweet seems to be less engaging, given that party tweets themselves are generally more neutral that personal ones.

(3) RT @LabourStafford: Euro campaign launch w/ @neenaformep @sionsimon @LW4WM @ansar_ali_khan @katevoteslabour @annieinclover @rowan_draper: h...

(4) RT @AnimalsCount: Results for London 21,092 for #AnimalWelfareParty. Sadly, no seat for us this time. Huge thanks to our amazing supporters...

(5) RT @AnimalsCount: @Djurensparti Best of luck for #EP2014 elections tomorrow. Let's Make History For Animals! #EU2014 http://t.co/Ru79J3rHnT
The last case that we will distinguish in this study is the retweet of a media
source (6):

(6) RT @Daily_Record: SNP EU candidate @TasminaSheikh outlines why she and many other Scots-Asians are voting Yes in the #indyref http://t.co/U...

This type of tweet can fulfil both functions of argumentation and contextualisation, but often in the form of quotation.

There are numerous cases of retweets of messages sent to candidates (analysed
in the previous section), as shown in example (7), in order to give them more vis-
ibility or to show the candidate being addressed in a positive light.

(7) RT @ARUKnews: @maryhoneyball Looking forward to the results of the EU elec-
tions. Thanks for your support for medical research #EU4Research

A quote thus deprived of a dialogical dimension can be seen as an instrument
of political approbation and argumentation and indeed this dimension is also
present in the cases of political parties (3) (4) (5).

3.4.3 The operator #

The hashtag is a specific sign that constitutes an important contextualizing el-
ement of Twitter discourse, characterized by its terse style. There are several
types of hashtags that can be distinguished according to content: #+phrase (1)
(a syntactically-structured utterance) or #+word-phenomena (2) (including ac-
ronyms and abbreviations).

(1) Is London ready to #VoteAnimalWelfareParty on Thursday at #EP2014 elections? Pls RT if you think yes! http://t.co/YQzlFHEhmj

(2) RT @GlenisWillmott: Labour MEPs fight for LGBT rights in the UK, EU and world-wide #EP2014 @LGBTLabour @LGBTintergroup http://t.co/U68vnykRXs

However, as in the case of the @ operator, it is not the type of hashtag that de-
termines its function, but the elements it introduces. Both hashtags in the first
example (1) present reduced verbal units that aim to contextualize the discourse.
The first conveys ideas linked to a particular cause, and the request to retweet
aims to encourage people to show their support for this cause. The second might
serve to increase visibility of the tweet to all people following the official #EP2014
hashtag. The potential reach of these hashtags is relatively high both because of
the wide audience reached by the second hashtag and by the incitation to fellow
supporters to retweet the message. The same hashtag used in the second exam-
ple (2), in a retweet, seems to be more about passing on information, as well as
associated references or argumentation through the link.
The dialogical potential of a hashtag also varies depending on its environment. Here are a series of examples using #VoteAnimalWelfareParty. The degree of implication in a dialogue is linked to the construction of the tweet:

(3) @leonalewismusic We want to write a new chapter of history for animals at EU elections this Thurs. Will u join us? #VoteAnimalWelfareParty

(4) @itvnews There's a revolution happening. Many Londoners are planning to #Vote-AnimalWelfareParty this Thursday EU elections. Are u following?

(5) This Thursday Londoners have the opportunity to write a new chapter in this history of mankind. Play your part. #VoteAnimalWelfareParty

(6) We need around 140,000 votes from across London to make history for animals on Thursday! #VoteAnimalWelfareParty http://t.co/YQzIFHEhmj

(7) Believe in a better world for all animals? RT this: #VoteAnimalWelfareParty EU Elections May 22 http://t.co/fWshQGIgKF

In these cases, the author tries to appeal to the audience by accompanying the hashtag with linguistic elements such as questions (3) (4) (7) and imperative forms (5). The direct address is a way of trying to increase levels of engagement.

(8) #bbcnews BBC commentators and reporters cannot seem to hide their obvious enthusiasm for UKIP

(9) #bbcnews why is it the bbc are avoiding talking about German results? Maybe it doesn't fit today's agenda as Euro skeptics only got 7 %

The hashtags that name the information source (8) (9) can be compared with previous examples using the operator @+name of a media source. The difference would appear to be that using @ is a way of seeking to interact with a media source, whereas the choice of # sets up a conversation *about* the media source, often to criticise it, which can possibly be seen as an invitation to dialogue, either with the representatives of the media source, or among Twitter users who may or may not agree.

The dialogical potential of a hashtag thus depends very much on the hashtag itself: a common hashtag will add visibility to a tweet, but possibly not create much interaction, whereas a more obscure one can be a way of targeting a message to a small group of insiders who don't necessarily follow one's account.

### 3.4.4 Use of media

When considering use of media in tweets, we can distinguish videos, photos and screenshots.<fnref n="22" /> In this chapter we focus solely on the use of photos which are

<footnote n="22">22 Screenshots of newspapers' sites with relevant information, most often a picture of a candidate, are common. Their use in a tweet may fulfil an argumentative function (reference to an external source) or be a means of self-promotion.</footnote>
the most common type of media in our global corpus. Photos allow politicians to illustrate their messages and to reinforce their impact on the audience, and can be perceived as having high argumentative and interactive potential, even if this has not been established empirically in the framework of the current study. We can distinguish apparently “spontaneous” photos and others which are more evidently “staged”. Examples of photos within the first category concern some sports events, photos of natural scenes or of political debates. The aim of this type of photo seems to be to create a degree of complicity with Twitter users who could potentially be witness to these events. Staged photos often concern events from the campaign trail, possibly aiming to allow absent followers to feel present alongside their candidate.<fnref n="23" />

In individual tweets, the most common way for politicians to introduce photos is: **introductory utterance + spontaneous/staged photo**. The dialogical potential of a photo seems to depend on the nature of this photo and on the content of the introductory utterance.

<figure><img src="image_28.png" /><figcaption>Photo 1</figcaption></figure>

Diane Dodds MEP @DianeDoddsMEP - 9 май 2014 г.

Fascinating visit earlier with @J_Donaldson MP at @Leckeydotcom
who provide posturally supportive products globally.

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>

This post (Photo 1) presents a composition of an introductory utterance that contains two @ communication operators: **with + @ + name of politician** and **@ + company name** and a **staged photo**, possibly in the hope of being retweeted, since the dialogical potential seems otherwise to be relatively low.

<footnote n="23">23 This distinction is of course largely artificial, since even “spontaneous” photos are planned and taken intentionally. The difference here is more precisely as to how explicit the staging appears to be.</footnote>
<figure><img src="image_31.png" /><figcaption>Photo 2</figcaption></figure>

Ansar Ali Khan @ansar_ali_khan 6 MAي 2014 r

At Villa Park watching and supporting our local team @SaltleySFC

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>

The second tweet also contains an @ communication operator: **@ + football club**, but takes the form of a **spontaneous photo** this time. By choosing this particular **@** mention and showing followers of the football team that he was present at the match, it can be assumed that this candidate was seeking to underline their shared allegiances, foregrounding his role of “ordinary” football supporter rather than his role of candidate.

It is interesting to note that the photos posted tend to constitute an integral part of the utterance (nominative sentence completed by Photo 1, elliptic sentence explained by Photo 2). Once again, the complementarity between the introductory utterance and the posted photo underlines the necessity for these two elements to be analysed together. Nominative sentences as illustrated by Photo 1 are recurrent:

(3) Great session with the best team in Birmingham in my own ward WWH + **staged photo**

(4) Lovely afternoon in Stafford with super PPC @kategodfrey @sionsimon @neena-formep @LW4WM and Stafford councillors + **staged photo**

(5) Fantastic 1st day of @balmoralshow – great conversations with people from right across NI & beyond. Roll on tomorrow + **spontaneous photo with a political actor**.

Another common type of introductory utterance: gratification element (thank you) + **spontaneous/staged photo**, # + **spontaneous/staged photo**, as for example

(6) Best wishes to the hundreds of cyclists that just passed my office in Lisburn who are #cyclingagainstsuicide + **spontaneous photo of a sports event**.
The spontaneous photos may seem to be more interactive because they can more
easily be shared and understood (2) (5) (6), while the staged photos (1) (3) (4)
seem to target Twitter users curious about a precise event. In all cases, both spon-
taneous and staged photos can be used to convey information or arguments.
Their interactivity can be measured only in conjunction with the analysis of an
introductory utterance that determines the targeted audience.

3.4.5 The use of links (http)

A hyperlink is a flexible communication operator whose function and associated
dialogical potential depend very much on its neighbouring elements, as the con-
tent of a shortened link is generally not immediately apparent. The vast majority
of links are coded by clickable shortened URLs, which provide few clues to their
target or content. This may or may not make people curious to click on them.
Sometimes the content of the link is directly integrated in a tweet (for example
videos from Youtube (1, below)). Politicians' links often lead to personal or party
sites, blogs or Facebook pages, whose objective appears to be to invite people to
adhere to their ideas.

There are different ways of introducing (a) **personal links** that lead either to personal sites (3), Facebook pages or profiles, (4) (5) (6), or blogs (2), which can be termed or (b) **external links** leading to external sources (1) (7) (8). The dialogical potential of these links depends in the first place on the neighbouring elements: other communication operators and/or other integrated elements (videos/click-able screenshots of media web pages). Tweets (1) and (2) below illustrate this. Tweet (1) includes an external link to YouTube, yet the whole tweet seems to be more interactive than the second one (2) that leads to a personal link. In spite of the presence of a gratification element, tweet (2) does not seem to address followers in particular, and is incomplete, with followers being implicitly encouraged to click on the link for more information. The first tweet (1) contains a hashtag and a question that seem to increase its dialogical potential, in association with the integrated video.

(1) Believe in a better world for all animals? RT this: #VoteAnimalWelfareParty EU
Elections May 22 http://bit.ly/1t3ebBU + **integrated video**

(2) Thanks: A big thank you to everyone who took the time and trouble to vote BNP yesterday. I would also like to... http://bit.ly/1jBUs9M

(3) The second in my week-long series of reasons to vote UKIP on Thursday. Send them a message! jonathanarnott.co.uk/2014/05/reason...
Examples (5) and (6) also contain personal links that lead to Facebook but seem to reveal higher dialogical potential than tweet (1) thanks to the neighbouring elements used, such as @ + **personal account name** (5) or question + integrated article (6). Even an external link to a media source as in examples (7) and (8) could be seen to be interactive depending on the neighbouring elements as @ + **personal account name** + integrated picture (8) or opinion + external link + integrated video (7).

(4) This is the last day before the vote to elect Members of the European Parliaments for Britain, and I cannot... http://fb.me/6qIBKclQD

(5) @meljomur @votingyes @Skooshbag @Celebs4indy I wasn't there unfortunately but this post covers general feedback m.facebook.com/story.php?stor...

(6) *Had enough yet? The system is broken.* http://fb.me/3a9Ba5Lby + **integrated article from Guardian**

(7) Didn't see it on tv news at all but at least @BBCScotlandNews have the pensions confirmed safe article posted on line m.bbc.co.uk/news/uk-scotla...+**integrated video**

(8) @ToniGiugliano on why we must be independent in Europe: heraldscotland.com/mobile/comment... #ep2014 + **picture**

In general we can note several strategies used by politicians in order to incite Twitter users to follow their personal sites or external links: imperative phrases (3), broken sentences (4), questions (6) or even direct addressing (8). The dialogical potential of a link does not depend on its nature but on the introductory utterance and the elements integrated afterwards. A link to Facebook or another social media account may also lead sympathetic Twitter followers to follow that account too, thus increasing the candidate's social media visibility and reach in general. The dialogical potential of tweets including social media links thus exceeds Twitter itself, since comments may be left on other platforms, after clicking on a social media link in a tweet.

**3.5 Discussion and conclusions**

The examples cited of the different communication operators and their functions tend to confirm the hypotheses formulated above. Hypothesis 1, concerning the importance of neighbouring elements in determining a communication operator's function can be validated thanks to the data studied. This suggests that Twitter style classifications should be based not only on the number of each type of communication operator used by a politician, but on the functions of the prevailing operator(s) as actualized in discourse by means of its accompanying elements. This in turn entails close, qualitative analysis of the tweets in question.
The second hypothesis, concerning the degree of implication in dialogue, is also supported by the data considered in this study, although the notion of “dialogue” clearly merits further investigation, which could be carried out by examining the retweets and conversations provoked by a given tweet. Despite this, the notion of implication or reach appears to be a meaningful criterion on which to differentiate tweets qualitatively, ranging from those whose dialogical markers (addressing, questions, exclamations...) and communication operators suggest that they are aimed at one or a few individuals, to those who seem to target a much wider audience. These differences in potential reach often seem to correspond to different strategies, ranging from “authentic” one-to-one dialogue – that Holy Grail of political communication on Twitter when one reads certain analyses – to the use of hashtags or at mentions which seem aimed to ensure a tweet’s visibility rather than to provoke direct exchanges with other users. There again, the contents of the tweet (more or less controversial, surprising, inspiring, etc.) and its dialogical markers, as well as the social and / or political context in which it is sent, all need to be taken into account in order to further characterise its dialogical potential.<fnref n="24" /> In order to analyse this potential, we propose the following table, applied to different operators, to resume, qualify and exemplify the differing degrees of dialogical implication.

<table><caption>Figure 4: the “I to I” Model</caption><thead><tr><th>Degree of implication in a dialogue</th><th>+++</th><th>++</th><th>+/-</th></tr></thead><tbody><tr><td>Dominant communication operator functions</td><td>Addressing, Mention, interaction</td><td>Referencing, argumentation</td><td>Passing on information, contextualisation</td></tr><tr><td>Goal/strategy</td><td>To involve other persons directly in discussion</td><td>To enter into a particular mini-public on Twitter</td><td>To share information</td></tr><tr><td>Audience concerned by the message</td><td>=&gt; limited number of Twitter users</td><td>=&gt; some groups of Twitter users</td><td>=&gt; large numbers of Twitter users</td></tr></tbody></table>

<footnote n="24">24 It should be further noted that this “potential” remains a prescriptive idealisation when based on an analysis of the dialogical features of the tweets themselves. Another way to approach the question would be to analyse the actual “impact” of the tweets in the Twittersphere, based on conversations and retweets (supra).</footnote>
<table><thead><tr><th>Degree of implication in a dialogue</th><th>+++</th><th>++</th><th>+/-</th></tr></thead><tbody><tr><td>Example<sup>25</sup></td><td>@CllrAlexander this for talks as a rally or a big work session?</td><td>RT @ChorltonGreen: RT @ranty_man: Hunt is desperately trying not to alienate former Labour voters #BBCQT; is it working?</td><td>#bbcnews BBC commentators and reporters cannot seem to hide their obvious enthusiasm for UKIP</td></tr><tr><td>Example of communication using operators</td><td>@+name of a person / question @+name of a person / gratification elements</td><td>#+question RT+personal commentary<sup>26</sup> @+party name</td><td>Popular # RT / @+name of a media source http[without other elements]</td></tr></tbody></table>

The acronym in “I to I Model” stands for “Information to Interaction”: often presented as the two extremes of a tweet’s potential functions. The model characterises the relationship between four key elements. (i) The **communication operator’s function** as mobilized in the tweet which defines (ii) the **audience potentially concerned** by that tweet. According to the audience potentially addressed or actually involved in a conversation, we can talk about (iii) the **reach** of a tweet. Based on the reach, (iv) the **relative dialogical potential** of the message can be estimated. This estimate is not numerical, but simply relative to other contextualised configurations of operators. The figure suggests that the degree of implication in a dialogue is inversely proportional to the number of Twitter users concerned by a tweet. Once actualized in a tweet, communication operators should give a key to understanding a politician’s strategy to reach his or her targeted audience.

Although the “I to I model” attempts to associate particular occurrences of operators and their neighbouring elements with different degrees of implication

<footnote n="25">25 It is not possible to show separate examples for each type of operator, because the functions are actualized by the way of correlations between different operators, thus to extract them from their context does not make sense.</footnote>

<footnote n="26">26 One particular limit to characterising the dialogical value of retweets is the difficulty of knowing whether a message is being quoted partially or not, and consequently distinguishing its different authors. While this is possible when working on a corpus, it is much more difficult for users in real time.</footnote>
in dialogue, we have already noted that this may vary considerably depending on other elements in the tweet and on the wider context. The model thus needs to be further developed and adapted to take into account these factors. Other limits to this preliminary study include sample size and representativeness, and the particular domain (political communication) from which the tweets were chosen. While we would argue that the general principle of taking into account the context of operator use remains equally valid for tweets from other domains of social activity (corporate communications, celebrity fandom...), it is clear that each of these domains is likely to reveal its own specificities.

Future developments of this model will go further into taking into account the use of embedded or linked media (photos, videos) in tweets, as this is a widely-used feature of the platform. The approach also needs to clarify how images relate to questions of dialogue and reach.

For all of its limits and the exploratory nature of this approach, we suggest that the “I to I” model opens up new possibilities to let us systematically investigate and characterise the dialogical qualities not only of single tweets, but also, by extension, of individual accounts, political parties, etc., in a more sophisticated way than many of the approaches currently presented in the academic literature. In this respect, we hope that it may help shed light on the ongoing debate in political communication into the relative “(im)maturity” of politicians’ use of the medium and the frequent denunciations of their “web 1.0 mentality”, whereby they prefer to broadcast information rather than interact. Looking at the relative reach or dialogical potential of their messages may enable us to distinguish more subtly between different strategies, taking into account the different communication functions which specific tweets might seem to fulfil, and the individuals or groups which they ostensibly target, be they political colleagues, journalists or media, activists, citizens, etc. If direct two-way politician-voter interactions may indeed be scarce, with whom do politicians more readily interact and what seems to motivate the different types of tweets they use? The answers to such questions will hopefully give us a more accurate vision of various logics of usage by politicians, which may then be fed back into the wider discussion about the possible construction of a deliberative digital public sphere and the degree to which the adoption of Twitter and other social networking sites by politicians may or may not renew democratic processes.
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# 4. Twitter et la politique : stratégies de communication de candidats et espace public

## Abstract

The chapter focuses on the tweets exchanged by two Italian candidates during the European election campaign, analysing how they are using Twitter as a political communication tool, and trying to define the “political tweet” in the light of the current political system.

## 4.1 Introduction

Traditionnellement Twitter est présenté comme « un service Web de microblogging permettant à ses utilisateurs de diffuser des messages limités à 140 caractères, de rediffuser et de répondre à ceux d'autres utilisateurs<fnref n="27" /> ». Inventé par Jack Dorsey en 2006 à San Francisco, ce service a pris de l'ampleur grâce à sa structure multifonctionnelle. Il a réussi à regrouper différentes fonctions avant séparées dans d'autres médias sur une seule interface.

Nous commencerons par nous centrer sur ce medium en tant que support en explorant ses fonctions communicationnelles et ensuite nous étudierons les pratiques de Twitter, les manières dont deux candidates italiennes aux élections européennes ont utilisé ce microblogging. Cette approche s'explique d'une part par la nécessité de comprendre comment ce medium dicte ses contraintes d'interaction avec les utilisateurs et oriente la communication de ses participants, de l'autre par la volonté d'analyser comment les candidates s'approprient ce support et s'expriment à travers leurs tweets. Peut-on vraiment parler de stratégies de communication à l'intérieur de l'agora de Twitter?

Nous nous intéresserons aux pratiques sociales dictées par ce support : peut-on examiner des « manières de faire » d'usagers ? Plutôt qu'approcher Twitter comme un texte en cherchant des limites presque impossibles à cerner, nous allons le considérer comme une pratique<fnref n="28" /> dans le sens qu'on s'intéressera au cours d'action

<footnote n="27">27 Emilie Ogez & Jean-Noel Chaintreuil, *Twitter, 101 questions*, Strasbourg, Ed. Diateino, 2012, p. 21.</footnote>

<footnote n="28">28 « On fera donc l'hypothèse que les pratiques se caractérisent et se distinguent principalement par le rôle du cours d'action dans la production de formes significantes, et spécifiquement des valeurs pratiques, suscitées et exprimées par la forme des cours d'action, dans le « grain » le plus fin de leur déploiement spatial, temporel, aspectuel, Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm - 978-3-631-69740-5</footnote>
que Twitter va produire, à la dynamique activée par ce medium. Ce sont les étapes de l'action qui produisent du sens, les objectifs que les utilisateurs vont atteindre et qui sont remaniés continument dans la pratique des usagers. Twitter est à ce propos un exemple pertinent pour l'observation des usages collectifs des réseaux sociaux et pour la construction du sens des « expériences en acte <fnref n="29" />».

Si Twitter dicte, sur le plan de l'expression certaines configurations figées (obligation d'écriture brève, emploi de symboles spécifiques, de hashtags, etc.), les candidats construisent-ils un *modus operandi* cohérent, spécifique à l'usage de ce microblogging ?

## 4.2 Le cadre de la recherche

Nous avons constitué et étudié un corpus de tweets échangés par les candidats italiens de la liste Tsipras et de celle du Movimento Cinque Stelle (M5S) pendant la campagne électorale européenne 2014³⁰. Notre corpus a été recueilli grâce à une méthode quantitative qui a pu rassembler les tweets et les hashtags envoyés par les candidats italiens des listes officielles de la campagne électorale européenne de 2014. Malgré l'utilisation d'un logiciel qui a rassemblé tous les tweets et les hashtags émis par les candidats de chaque liste de différents pays d'Europe (Allemagne, Angleterre, Belgique, Italie, Espagne), nous avons choisi, dans ce papier, de nous focaliser sur un seul pays : l'Italie.

La multiplicité des données a permis une analyse comparative des corpus dans la volonté de comprendre les styles des campagnes électorales, le croisement des stratégies des candidats et l'étude des contenus des tweets échangés<fnref n="31" />. Twitter est-il un outil d'autopromotion des candidats ? S'agit-il d'une nouvelle façon de rester au plus près des électeurs ?

Pour le moment, nous allons nous concentrer sur une analyse qualitative en rassemblant les tweets envoyés par quelques représentants italiens de la liste Tsipras et celle du Movimento Cinque Stelle (M5S).

modal et passionnel », J. Fontanille, « L'analyse du cours d'action. Des pratiques et des corps », NAS, 114, 2011, consulté le 28/06/2015.

<footnote n="29">29 Pour un approfondissement sur la pratique en sémiotique, je renvoie à J. Fontanille, Pratiques Sémiotiques, Paris, Puf, 2008, p. 26.</footnote>

<footnote n="30">30 Il s'agit du projet ANR (2012-2015) « Twitter at the European Elections 2014 » (TEE 2014), piloté par le laboratoire CIMEOS de l'Université de Bourgogne (A. Frame). Cette étude réunit différents laboratoires internationaux autour de la question « Formes et fonctions de participation politique dans un monde numérique ».</footnote>

<footnote n="31">31 La récolte des données s'est achevée une semaine après le vote européen le 1er juin 2014.
Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm - 978-3-631-69740-5</footnote>
Enfin, le but ultime de cette recherche sera celui de comprendre la nature d'un tweet politique, si l'on peut en parler à juste titre pour comprendre ses conditions d'existence et d'échange. Pourquoi certains tweets sont-ils plus suivis ou retweetés que d'autres ? Quelles sont les conditions de succès d'un tweet ?

## 4.3 Twitter: structure, matérialité et fonctionnalités

Chaque forme de média se caractérise et se distingue de ses pairs à la fois par son support et par les fonctionnalités qui lui sont spécifiques. Pour comprendre les contraintes d'un medium, dans sa composante paradigmatique et surtout dans ses déploiements syntagmatiques, nous souhaitons, comme précédemment annoncé, nous occuper du microblogging Twitter en l'appréhendant à différents niveaux.

Tout d'abord, nous allons partir de certaines contraintes matérielles et fonctionnelles de Twitter pour comprendre l'influence et l'incidence du support sur son emploi par les usagers (ergonomie de l'interface, accessibilité, points d'intervention, etc.). Il s'agit notamment de s'intéresser aux outils techniques mis à disposition par le système informatique même permettant de « faire-faire », au sens sémiotique du terme<fnref n="32" />, à l'usager différents parcours actantiels.

Ensuite, en recentrant l'attention sur son aspect communicationnel, nous tenterons de caractériser Twitter par rapport à d'autres médias. À partir de ce medium multimodal déterminé comme d'autres par la présence de l'image, de l'écrit, du son et de liens interactifs, nous allons comprendre les interactions qui seront induites par Twitter et qui vont le différencier du SMS, du chat ou de l'email. Il s'agit de comprendre les usages générés par ce support qui le déterminent par rapport à d'autres, dans sa circulation médiatique. Twitter peut par exemple parader la même structure rhizomique typique des réseaux sociaux mais seulement certaines de ses fonctionnalités peuvent être activées par rapport à d'autres supports médiatiques.

Après l'inscription obligatoire sur le site (twitter.com), l'utilisateur a la possibilité de personnaliser son profil avec une phrase (un slogan), un avatar et comme dans d'autres interfaces, customiser sa « mise en scène de soi <fnref n="33" />». Le contrôle du profil reste semblable à d'autres interfaces comme Facebook dont on peut, dans l'onglet accueil, connaitre le nombre de tweets envoyés, les abonnements, les abonnés et retweeter un message. Déjà parmi ces premières possibilités, il

<footnote n="32">32 A. J. Greimas/J. Courtés, *Dictionnaire raisonné des sciences du langage*, Paris, Hachette, 1979.</footnote>

<footnote n="33">33 E. Goffman, La mise en scène de la vie quotidienne. La Présentation du soi, Paris, Ed de Minuit, 1973.</footnote>
s'instaure un pouvoir faire commun soit au courriel soit à la messagerie instan-
tanée ou chat : l'écriture et l'échange. Il s'agit d'un vrai binôme : l'un n'a plus de
sens aujourd'hui sans l'autre. Plus que pour l'échange épistolaire traditionnel, on
assiste à un « dialogue écrit » en temps réel, marqué, comme pour Facebook, par
la réciprocité et l'instantanéité.

Pour ce qui concerne le retweet, nous pouvons parler d'une vraie et propre pratique d'usage<fnref n="34" /> dans le sens que l'internaute fait une expérience des textes dans sa sélection, dans sa manipulation<fnref n="35" /> et dans la ré-énonciation. Le retweet est la republication d'un tweet d'une autre personne, jugé particulièrement intéressant par son contenu. Il s'agit d'un partage ciblé aux abonnés (aux followers) ou à une liste (à un groupe de personnes plus ou moins restreintes réunies par une ou plusieurs thématiques communes) ou à l'ensemble du réseau. Le symbole « RT » signifie bien que la personne n'est pas auteur du message mais un simple véhicule de transmission de l'information. Cette opération, qui à l'intérieur d'un courriel est une procédure relativement banale, sur Twitter prend une autre signification. L'usager qui décide de retweeter n'abuse pas de cette procédure. Le principe n'est pas celui d'une rediffusion massive mais au contraire ciblée et marquée par une valeur ajoutée. Le message retweeté apporte de l'appréciation, du crédit soit à son auteur soit à la personne qui « trie » l'information en la diffusant. Cette valeur est simplement la marque énonciative RT souvent suivi d'un ajout, d'un commen-
taire ou de quelques mots emphatiques qui ont le but de renforcer le texte source. L'utilisateur peut ajouter au texte du retweet un commentaire et signer le texte en le personnalisant. Cette procédure peut se réaliser maintes fois. Une question se pose : à qui appartient le contenu textuel d'un tweet ?

Toujours dans l'onglet d'accueil, l'usager peut écrire un message privé à un autre usager ou un tweet visible, sauf restrictions particulières à tout le monde. La restriction de 140 caractères est toujours valable, détail qui le différencie du mail ou de Facebook où l'espace d'écriture est majeur. Nous pouvons considérer le tweet comme une forme brève de communication dans le sens décrit par I. Pez-
zini : « Il s'agit de formes délibérément mineures, où le mineur n'est pas un repli
mais un genre comme un autre<fnref n="36" /> ». Les tweets sont des textes autonomes contenant
des supports multimodaux tenus ensemble par une même source énonciative :
l'énonciation du tweet.

<footnote n="34">34 J. Fontanille, *Pratiques sémiotiques*, PUF, 2008.</footnote>

<footnote n="35">35 A. J. Greimas/ J. Courtés, *idem*, 1979.</footnote>

<footnote n="36">36 I. Pezzini, *Trailer, spot, siti, banner*, 2002, p. 17. (traduction personnelle).</footnote>
Twitter ne permet pas la constitution de groupes privés gérés par un seul leader mais cela ne signifie pas que certains followings (personnes que l'utilisateur a décidé de suivre en s'abonnant à leur compte) n'assument pas ce rôle. L'effet « avalanche » reste présent dans Twitter du moment que plus un usager est suivi plus il sera connu, diffusé, lu et en tout cas présent dans le réseau. La gestion du profil public/ privé relève de ce que D. Cardon appelle le modèle de visibilité « post-it ». Selon l'auteur, « les participants rendent visibles leur disponibilité et leur présence en multipliant les indices contextuels, mais ils se réservent leurs accès à un cercle relationnel restreint <fnref n="37" />». C'est le cas de Twitter, caractérisé par une panoplie d'indices laissés par les utilisateurs comme la localisation géographique permanente et leur présence soulignée par la mise à jour de leurs tweets postés en temps réel. Pour continuer à favoriser l'échange écrit Twitter impose dès l'inscription, l'emploi d'un pseudonyme suivi du symbole de l'arobase (@). La valorisation de l'écrit, comme pourrait être pour d'autres sites celle de l'image (par exemple Flickr), passe aussi par la reconnaissance de mêmes symboles qui facilitent l'interaction en étant déjà employés ailleurs.

Enfin, une des dernières fonctionnalités de ce blogging qui se présente à l'utilisateur, est l'onglet nommé « découvrir ». Il se remarque par cinq possibilités. L'usager se trouve dans la position de choisir des propositions déjà filtrées par ses connaissances, il peut s'abonner aux contacts favoris de ses amis ou laisser à Twitter la suggestion de thématiques les plus retweetées du moment. Nous observons différentes sections : une première nommée « tweets » qui regroupe « Ce qui se passe en ce moment, personnalisé pour vous <fnref n="38" />». Il s'agit d'un choix de tweets, les plus diffusés, sélectionnés selon la localisation géographique de l'utilisateur. L'information est proposée par des followers que l'usager suit régulièrement, elle est « triée » par d'autres usagers et annoncée presque en temps réel sans « effets d'annonce » particuliers. Deuxièmement, nous trouvons la section « activité qui permet de voir ce que les autres usagers ont fait, modifié de leur compte », affichant les nouveaux tweets dans la time-line (TL) de l'utilisateur. L'inactivité est bien évidemment bannie de cette rubrique parce que la mise à jour instantanée, la découverte d'un tweet curieux et insolite est le but ultime. La concurrence s'exprime par un simple commentaire ou par une énonciation de ce qui est déjà connu. Il s'agit de souligner ce qui est arrivé dans le monde entier. La fonction phatique de Jakobson<fnref n="39" />, la volonté de maintenir le contact avec l'usager par le

<footnote n="37">37 D. Cardon, « Le design de la visibilité : un essai de typologie du Web 2.0 », *Internet Actu.net*, 01/02/2008, consulté le 05/06/2014.</footnote>

<footnote n="38">38 https://twitter.com/i/discover, consulté le 05/06/2014.</footnote>

<footnote n="39">39 R. Jakobson, *Essais de linguistique générale*, Paris, Ed. de Minuit, 1963.</footnote>
simple fait d'être présent sur le réseau, est un des objectifs de Twitter. Ce qui fait
dire à Ogez & Chaintreuil : « assez rapidement le slogan de Twitter est passé de
'What are you doing ?' à 'What's happening ?'<fnref n="40" /> ».

La troisième possibilité comprend les « suggestions », le suivi en temps réel des comptes abonnés et d'autres nouveaux susceptibles d'intéresser l'usager pour leur affinité thématique. Cet onglet se présente comme une liste de propositions sous forme d'un menu déroulant marqué par la postille « suivre ». Cette dernière est prête à être activée par l'utilisateur. Un simple clic permet d'initier l'abonnement et suivre le flux continu des tweets. Le libre accès à cette fonction invite l'utilisateur à entrer dans d'autres comptes en sachant que plus il sera abonné, plus il aura la possibilité de participer à l'univers de Twitter en tant que membre actif.

Le quatrième onglet rassemble les « comptes populaires » les plus suivis par l'actualité contemporaine. Cette liste d'adresses non exhaustive change au fur et mesure de l'actualité. Elle est divisée par genre comme par exemple : la musique, le sport, l'humour, la télévision, le divertissement, la politique, les voyages, etc. Elle présente une différente organisation de l'information par rapport à l'onglet « suggestions ». Il s'agit toujours d'évoquer, jamais de contraindre, des comptes à suivre mais d'une façon indirecte en présentant des sujets assez larges, traités par différents comptes. Par exemple pour la thématique « semaine des musées » nous trouvons la possibilité de s'abonner aux accounts des musées majeurs européens. Ces suggestions se présentent, au contraire des comptes, sous forme d'un menu horizontal visible que par les photographies des accounts. Il s'agit de la carte de visite du compte officiel, la marque de fabrique de l'institution ou d'un privé. Ce regroupement est encore plus large et exhaustif que le simple compte en permettant de découvrir et implicitement de s'abonner à un ensemble de followings. Différentes logiques opposent ces deux possibilités de découverte des nouveaux comptes : la première recherche un compte spécifique qui ensuite peut renvoyer à d'autres similaires, la deuxième s'ouvre à une thématique générale pour trouver des comptes spécifiques privés ou publics. Le but est par une voie ou par une autre d'intéresser les usagers en proposant deux parcours narratifs différents. Le premier concerne l'usager qui sait quoi chercher, un compte précis d'un following et qui arrive directement à sa source d'information. Le seconde s'adresse à l'utilisateur intéressé par un thème mais curieux de découvrir des propositions similaires, ouvert à différentes possibilités en restant focalisé sur un sujet précis.

Nous pourrons ajouter dans la barre horizontale du menu de Twitter l'onglet « rechercher » qui reste toujours présent dans la structure du site pour pouvoir

<footnote n="40">40 *Idem*, 2012, p. 22.</footnote>
explorer l'univers des informations. Le recherche se fait par simple écriture d'un mot-clé précédé ou pas par le hashtag « # ». Ce symbole, redevenu à la mode (2007), permet d'annoncer un mot-clé qui regroupera la thématique indiquée et tous les tweets envoyés par les twitteurs contentant ce sujet. La fonction de l'hashtag est englobée dans une tension permanente entre informer l'usager d'une manière précise sur le sujet et trouver d'autres utilisateurs avec lesquels interagir sur le même centre d'intérêt<fnref n="41" />. Le hashtag semble condenser quelques fonctions typiques du titre : la fonction d'identification et celle intertextuelle<fnref n="42" />. La première permet de comprendre de quel sujet le tweet va traiter ; en revanche le contenu textuel n'appairait pas au lecteur. L'usager doit cliquer sur le hashtag pour pouvoir y accéder et lire son contenu. Cette dématérialisation du texte ouvre des ambigüités sémantiques par rapport à l'emploi plus « traditionnel » du titre dont le texte suit, à l'intérieur la même page, le titre. Le hashtag appairait comme un mot-clé condensant plusieurs arguments qui fait référence à une multitude de plans du contenu. Comme le souligne Hoeck : « Il existe pour tout titre une phrase expliquite performative qui doit avoir la forme suivante : «je déclare à toi que ce texte s'appelle X». A la surface nous ne trouvons que X<fnref n="43" /> ». Il s'agirait pour l'auteur de l'apparition sur le plan de l'expression du titre qui se présenterait comme un indice et une condensation du texte dont le plan du contenu serait beaucoup plus large qu'un texte traditionnel.

La deuxième fonction, d'ordre intertextuel, est plus exploitée par le hashtag et le microblogging Twitter plus en général. Le hashtag est mis en relation avec les autres textes circulant à l'intérieur du réseau Twitter et potentiellement avec tous les liens hypertextuels présents dans les tweets. Il entre en dialogue avec d'autres textes que seul l'usager va activer en construisant son parcours textuel. Nous pouvons parler d'une pratique exploratoire du texte qui désormais repose sur une structure « rhizomatique » et non plus linéaire.

Brièvement le cinquième onglet offre la possibilité de « trouver des amis » en important les contacts de ses propres adresses électroniques ou en invitant un ami à découvrir Twitter.

<footnote n="41">41 Nous avons différents sites qui aident les usagers à trouver les hashtags plus populaires et à en créer d'autres selon les buts recherchés comme par exemple hastags.org, hastagify.me ou wthashtag.com.</footnote>

<footnote n="42">42 Leo.H. Hoeck, « Pour une sémiotique du titre », *Documents de Travail et prépublications* XX-XXI, Centro Internazionale di Semiotica e Linguistica, Université de Urbino 1973, pp. 1-48.</footnote>

<footnote n="43">43 *Idem*, p. 25.</footnote>
L'importation de liens faibles44 qui sont en réalité les plus présents sur les microblogging, alimentent automatiquement le site de Twitter qui vit grâce à cet afflux constant de réseautage amical.

Nous avons pu expliquer quelles sont les caractéristiques de cette « page-écran »45 et les points d'intervention46 du site, qui techniquement permettent de faire intervenir le sujet sur l'interface graphique de Twitter. Ce microblogging qui cherche « à éveiller un vouloir »47 dans notre cas spécifique de connaissances, de nouveautés et plus globalement d'information.

Nous allons comprendre à travers quelles stratégies de communication ce vouloir se met en place pour favoriser le fameux « clic » ou abonnement aux followings.

## 4.4 Twitter en action : focus sur les fonctions communicationnelles

Si concrètement la gestualité requise par l'interface de Twitter reste relativement simple (déplacement avec la souris et clic sur les liens, pratique commune aussi à d'autres supports électroniques), la communication avec l'usager se met en place de diverses façons.

Tout d'abord, dès la création d'un compte Twitter, l'usager voit apparaître dans son profil le texte suivant :

Prenez 2 minutes afin que Twitter soit plus proche de vous. Notre suggestion : suivre plus de personnes. Oui, plus. C'est grâce à vos abonnements que vous construirez votre fil d'actualité. Construire un bon fil est au cœur du fonctionnement de Twitter. En construisant un fil qui vous reflète ainsi que vos intérêts, vous verrez avec quelle rapidité Twitter devient une partie inestimable de votre vie48.

L'utilisateur est placé au centre du processus de communication en devenant actant49 de la construction de son réseau. Ce qui est demandé est d'accomplir

<footnote n="44">44 Pour la distinction entre liens forts et liens faibles je renvoie à A. Casilli, *Liaisons nu- mériques, Vers une nouvelle sociabilité?*, Paris, Seuil, 2010.</footnote>

<footnote n="45">45 Nicole Pignier, « De la vie des textes aux formes et forces de vie. Texte, sens et com- munication, entre esthésie et éthique », Revue *Actes Sémiotiques*, Ouvrage de HDR, Presses Universitaire de Limoges, http://epublications.unilim.fr/revues/as/4786, 2012, p. 126. Consulté le 06/06/2014.</footnote>

<footnote n="46">46 Nous empruntons cette expression à A. Zinna, « Les objets d'écriture et leurs interfaces. Textes interactifs et hypertextes. Décrire et comparer les nouveaux phénomènes de sens », ouvrage de HDR, Limoges, 2001.</footnote>

<footnote n="47">47 Nicole Pignier, *idem*, p. 113.</footnote>

<footnote n="48">48 https://twitter.com/, consulté le 06/06/2014.</footnote>

<footnote n="49">49 A.J. Greimas/J. Courtés, *idem*, 1979.</footnote>
une performance grâce au vouloir faire de l’usager. Twitter favorise un accès facile au contenu informatif. Le sujet possède tous les outils techniques comme le moteur de recherche, la découverte des hashtags, le classement par genre pour se construire son propre savoir personnalisé selon ses goûts et ses envies. Le but officiel de ce microblogging est apparemment celui de s’informer et de se tenir au courant de l’actualité mais en réalité le savoir se construit en tant que partage de contacts, de circulation et ensuite de connaissances. L’idée de partage est valorisée beaucoup plus que le contenu de ce qui est véhiculé. La métaphore omniprésente de l’icône Twitter, un oiseau qui gazouille, qui survole et qui émet de courts messages semble bien représenter l’esprit du réseau. La centralité de l’échange ne signifie pas forcément partage de l’information. L’individu est un transmetteur de l’information et un interprète de cette dernière. La charge émotionnelle, le ressenti véhiculé, les prises de position permettent de faire émerger des « leaders d’opinion<fnref n="50" /> » très actifs, à court et long terme, à l’intérieur du microblogging. Par exemple, les tweets peuvent contenir de brefs textes de 140 caractères suivis de liens électroniques abrégés ou pas qui permettent de retrouver l’intégralité du propos sur d’autres pages web, ou simplement incitent à visionner des fichiers multimédias (photos, vidéos, fichiers sonores) hébergés sur d’autres sites. Ces pages renvoient souvent à des pages personnelles qui explicitent les idées et invitent à « approfondir » le profil de la personne.

La rapidité et l'instantanéité sont les mots d'ordre de Twitter. Les informations se présentent sous forme d'agence de presse, presque en continu du moment que le nombre d'abonnements s'élargit et que la personne ajoute ses contacts. Ce format est désormais présent sur les chaines d'information télévisuelles et à la une des journaux en ligne sous forme de « flash ». Nous avons différents exemples de circulation rapide de l'information à travers Twitter pendant des situations de révolution politique ou de catastrophes naturelles<fnref n="51" />.

L'association de fonctions communes au courriel comme celle de répondre, de fowarder, de bloquer ou d'inscrire le tweet dans les « favoris », implique la reprise de la communication écrite associée à un moteur de recherche interne à Twitter et à ses utilisateurs.

<footnote n="50">50 Nous faisons référence aux théories de E., Katz & P. Lazarsfeld, (2008), *Influence personnelle*. Paris: Armand Colin (1955: Personal Influence, New York: The Free Press).</footnote>

<footnote n="51">51 Nous faisons référence à l'article de Z. Dahmen-Jarrin, « Tic et mouvement social en Tunisie. Le rôle du téléphone portable et de Twitter dans la mobilisation », *La communication électronique dans la société de l'information*. Quels usages, quelles pratiques ?, sous la dir. de S. Zlini & F. Liénard, Ed. Klog, Mont-Saint-Aignan, 2012, p. 165-174.</footnote>
Les messages plurisémiotiques se succèdent les uns simultanément aux autres. Le microblogging les relie ensemble dans un réseau intertextuel en créant un macro-texte en évolution perpétuelle.

## 4.5 Le tweet politique

L'emploi du twitter en politique concerne au moins trois sphères différentes<fnref n="52" /> :

1) Les politiques en sens strict, les candidats mêmes (seule partie ici de notre analyse)

2) Les bloggeurs, les personnalités médiatiques, les stratèges de campagne autour des candidats

3) Les organisations qui couvrent la sphère politique

Déjà avec ces données, nous voyons que le champ d'investigation s'élargit de plus en plus.

Un premier point à souligner est malgré le fait que nous analysions un tweet d'une façon spécifique et en « autonomie », nous ne pouvons pas penser qu'il ne soit pas lié à un contexte précis et à un éventuel échange communicationnel qui se caractérisent par une interaction et une thématique spécifique. Ce type d'échange (au moins une émission d'un tweet et une réponse au dit tweet) n'est pas très fréquent dans les tweets de nos candidates qui n'instaurent pas beaucoup d'échanges communicationnels avec leur public. Par contre, ce sont les interactions entre twitteurs qui construisent le champ sémantique et qui définissent l'interaction même et la textualité qui reste par définition ici « ouverte ». En effet, l'écriture des tweets et l'émission des tweets autour du même argument créent une circulation de l'information éphémère qui permet de reconstruire au moins une isotopie. En tant qu'utilisateurs nous comprenons la thématique discutée et les expressions d'un certain nombre de candidats autour d'un thème spécifique.

Toutefois, il faudrait poser une question « Qu'est-ce que un tweet politique » ? Il n'est pas si évident de le définir mais si l'on reste sur l'idée que le dispositif même limite le contenu du tweet, nous pouvons soutenir qu'un tweet politique est un tweet attribuable aux accounts officiels des figures politiques dans un moment historique donné appartenant officiellement à un parti politique précis. Cette définition se veut encore vague mais le contenu lui-même ne peut pas être utile à la définition même. Encore, le tweet politique émis ou retweeté par le candidat est une sélection de l'information publique que le /la candidat(e) diffuse ou relance autour

<footnote n="52">52 Inside the Political Twittersphere A look inside Twiter's use for politics, October 2009
By Sysomos Inc. Alex Cheng, Mark Evans and Nick Koudas, consulté le 27/06/2015.
Alex Frame, Arnaud Mercier, Gilles Brachotte and Caja Thimm - 978-3-631-69740-5
Téléchargé de PubFactory à06/10/2021 11:57:11AM
via free access</footnote>
d'un évènement concernant la sphère publique à un moment précis. Souvent il s'agit d'un événement qui marque l'actualité et que le candidat va reprendre pour commenter ou l'employer comme cible polémique et pour proposer une contre réponse. Il aurait au moins deux emplois majeurs du Twitter imputables la sphère politique mais expansibles au fonctionnement même du médium. D'une part, on assiste à la diffusion ou rediffusion d'une information, souvent pas commentée et qui provient d'autres sources médiatiques. Il s'agit de remettre dans l'arène publique une nouvelle qui a été divulguée sur d'autres médias ou même sur Twitter mais qui est republiée sans commentaire de la part de l'expéditeur. Ce dernier rend visible sa source primaire, grâce aussi aux hashtags, et devient un simple diffuseur de la nouvelle. Les marques subjectives sont présentes à travers l'adresse Twitter de l'utilisateur et la personnalisation du profil. La communication se construit, ici, plus comme une caisse de résonance, de diffusion d'une thématique qui pourra s'élargir très vite et alimenter l'écriture des tweets. Ce n'est pas le contenu qui souvent fait rebondir l'information mais la rediffusion qui réactive le mécanisme de circulation même. Le retweet n'implique pas forcément un commentaire, ni une prise de position mais une réactivation à un moment précis d'une actualité souvent provenant d'ailleurs (presse en ligne et/ou papier, d'autres sites internet). Ce phénomène qui est consubstantiel au médium a instauré une vraie pratique, un vrai faire-faire à l'utilisateur. Elle prend le nom de retweeter.

D'autre part pour ce qui concerne le deuxième emploi, une intervention directe d'un twitteur est une prise de parole immédiate sur un évènement ou en tout cas l'expression d'une opinion. Le medium, vu les contraintes de 140 caractères, ne permet pas de formes d'expression longues mais plutôt succinctes grâce aussi à la présence de hashtags qui réduisent l'espace d'expression. Les prises de position directes et à la première personne n'encouragent pas forcément le dialogue ou la construction d'une interaction dialogique. Le tweet peut recevoir des réponses ou pas, peut être transféré ou pas ce qui dit de son intérêt peut-être ou de son succès médiatique.

En tout cas, le contenu du tweet n'implique pas forcément de réponses de formes d'interaction. Si l'on peut se permettre une métaphore un peu triviale, on pourrait comparer le tweet à une bouteille à la mer : son contenu circulera certainement mais il pourra être ou pas relevé. A ce propos, Cervulle et Pailler, en citant G. Deleuze, parlent de « production de rapports d'affection<fnref n="53" /> ». Les auteurs sou-

<footnote n="53">53 M. Cervulle & F. Pailler, « #mariagepourtous : Twitter et la politique affective des hashtags », *Revue Française des Sciences de l'Information et de la communication*, [En ligne], 4 | 2014, mis en ligne le 15 janvier 2014, consulté le 20 mai 2015. URL : http://rfsic.revues.org/717.</footnote>
lignent que « Affecter c'est exercer une force au sein d'un champ de relations. Ap-
préhender les réseaux sociaux numériques comme le lieu de rapports d'affection
permet de considérer que les échanges en leur sein dessinent des lignes de tension
et de partage aussi bien au niveau des sociabilités que des discours ». Il s'agirait de
travailler plus sur les rapports qui se tissent entre les différents échanges autour
d'une thématique que sur l'argument principal. On pourrait conclure qu'un tweet
réussi est celui qui a été retweeté et qui a « touché » un large public.

Pour Twitter, tweeter (écrire), retweeter (rediffuser, partager un contenu), être un follower d'un account (suivre une personne ou une liste de diffusion) font partie de la participation en ligne. Les degrés de cette « participation<fnref n="54" /> » plus ou moins actifs ou passifs, permettent globalement de suivre des traces de visibilité et de présence de l'internaute à l'intérieur du microblogging. En tout cas le suivi des débats politiques sur Twitter ne se résume ni à l'activisme politique ni à la circulation de l'information hors ligne. Même si l'on peut trouver des rapprochements et des compénetrations continues entre les deux sphères, pour comprendre en quoi les réseaux sociaux influencent les comportements politiques, nous sommes obligés d'étudier des pratiques d'usager en ligne mises en relation avec des supports médiatiques qui révèlent de la même substance de l'expression : le médium internet et en particulier le web 2.0, c'est-à-dire les réseaux sociaux.

4.6 Un rappel des bonnes pratiques

Ce que nous intéresse ici est de rappeler d'une façon très succincte les quelques
règles de bon usage qui sont instaurées par Twitter même, pour « avoir succès »
et réussir ses propres tweets<sup>55</sup>. Il existe une pléthore de manuels de conseils et
d'astuces de la création d'un compte jusqu'à son bon fonctionnement. Brièvement,
nous pourrions dire que :

1) Indispensable est le choix de sa propre ligne éditoriale : partager des informations appétissantes et centrées sur un domaine pointu

2) S'exprimer à travers des mots-clés représentatifs de la personne et d'un contexte. La personne sera plus facilement « re-diffusée »

3) Promouvoir une animation quotidienne et un engagement du 70 % (informa-
tions), 20 % (réponses aux followers, interaction), 10 % (messages personnels)

<footnote n="54">54 La notion de participation a fait couler beaucoup d'encre. A ce propos on renvoie pour une synthèse du débat à Ch. Barats, *Manuel d'analyse du web*, Paris, A. Colin, 2013, p. 171.</footnote>

<footnote n="55">55 Un exemple parmi d'autres : Jean-François Belmonte, *La vie en 140 caractères*, 2013.</footnote>
4) Respecter les créneaux horaires pour l'mission de tweets : 6h-7h le matin, la pause déjeuner, 17h-18h le tard après-midi et, au maximum 21h le soir (le retweet est recommandé en fin de soirée)

5) Adopter la bonne place pour le lien hypertextuel qui devrait se placer au 25 % de longueur du tweet et pas à la fin

6) Employer les applications liées à Twitter comme : tweetreach.com qui permet de connaître le nombre de fois où un tweet ou un hashtag a été mentionné et également le nombre de personnes potentiellement touchées ; crowdbooster. com qui aide à suivre le nombre de followers dans le temps, de mentions et de retweets; tweetWhen.com pour savoir quand nous sommes plus retwee-tés, tweriod.com pour connaître si les followers ont retweetés les messages, clocktwetts pour programmer l'envoi de tweets, etc.

Ces quelques lignes de bonne conduite ne sont pas forcément suivies par les candi-dates de notre corpus qui semblent plutôt poster des tweets dans l'immédiateté et particulièrement pendant les événements dont ils ont le rôle de participants actifs (meetings, débats politiques, présences à l'ecran). La construction d'une image médiatique des candidats se réalise aussi à travers ce microblogging qui grâce à son instantanéité permet un semblant de participation « live » des followers à la sphère politique et renvoie une image de forte activité de ses participants.

## 4.7 Analyses des pratiques des candidats : le cas E. Forenza

Comme annoncé précédemment, nous allons repérer des pratiques d'usage de Twitter des candidats aux élections européennes du 22-25 mai 2014. Pour ques-tion de praticité et de méthode qualitative nous ne pouvons pas faire un parallèle entre tous les candidats des partis participants à cet événement politique. Nos analyses se veulent sur le plan de l'immanence, ponctuelles, circonscrites autour d'un évènement précis.

Nous nous consacrons à deux candidates femmes : Eleonora Forenza inscrite au Parti communiste italien, candidate de la liste Tsipras pour le Sud d'Italie et Isabella Adinolfi pour le Mouvement Cinq Etoiles (M5S) pour le Sud d'Italie aussi. Nous avons comparé les deux candidates parce qu'elles étaient suivies presque par un nombre paritaire des followers (3.546/4.393) aujourd'hui<fnref n="56" />, pour leur âge similaire (1976/1978), parce qu'elles sont inscrites à Twitter depuis la même pé-riode (février 2012) et parce qu'elles appartiennent à deux partis différents de la sphère politique de gauche.

<footnote n="56">56 Septembre 2015.</footnote>
Nous nous sommes limités à une petite incursion dans le domaine politique, même si bien d'autres seraient possibles, pour comprendre les tweets qui s'insèrent dans ce champ et pour comprendre les relations autour de ces derniers.

Les tweets recueillis débutent le jour du dépôt par le gouvernement italien des listes officielles, le 25 avril 2014, jusqu'à une semaine après les élections, le 1er juin 2014.

Nous allons commencer par regarder de plus près les tweets émis et échangés (retweets) sur le profil Twitter de la candidate E. Forenza dans la période citée. A l'époque, la candidate est suivie par 1.600 followers et se présente en tant que « chercheuse précaire féministe, communiste, qui vit dans le sud de l'Italie, qui aime Gramsci et Lonzi et le pop des années 80 »<fnref n="57" />. La volonté de mêler l'appar- tenance politique de la candidate (Liste Tsipras) avec ses gouts personnels et ses « maîtres à penser », démontre une approche d'« exposition personnelle » avec ses followers. Une stratégie confidentielle, proche des électeurs qui voie l'élue s'adres- ser aux internautes dans la volonté de les impliquer dans le combat pour Alexis Tsipras : « Oggi partecipiamo come delegazione dell'@altraeuropa ConTsipras alla riunione del GUE. restiamo uniti, e uniamo ciò che il neolib ha diviso!<fnref n="58" /> » ou « Dopo la riunione dei candidati, una conferma : l'@altraeuropa continua! Abbia- mo una grande responsabilità: non disperdere il lavoro fatto!<fnref n="59" /> ». Les tweets émis par la candidate soulignent, même après élections, la promesse de changement prise par la liste, la volonté d'entreprendre un combat collectif et le sentiment d'appartenance à une collectivité qui partage des valeurs proches.

Pour ce qui concerne les tweets, nous pouvons affirmer que du début du mois de mai à la fin, la candidate a augmenté son nombre de tweet, grâce à une écriture directe et continue qui marque sa présence sur ce microblogging. Le nombre de tweet a progressé d'une manière constante. La candidate émet plus d'un tweet (une moyenne de 5) par jour. Ces derniers sont émis avec une fréquence très rappro- chée (quelques minutes) sans avoir forcément une unité thématique commune. Il

<footnote n="57">57 En réalité le terme italien que l'élue a employé pour indiquer les régions du sud de l'Italie relève plus de l'oralité et de l'expression familiale que d'un langage “ politique-ment correct”. Nous ne pouvons pas nous étaler sur les variations du langage oral/ écrit, partie qui resterait très intéressante à approfondir.</footnote>

<footnote n="58">58 Published the 10 June 2014 by E. Forenza: « Aujourd'hui nous participons en tant que délégation de l'altraeuropa con Tsipras à la réunion GUE. Restons unis et unions ce que le néolibéralisme (néolib) a divisé », (traduction personnelle).</footnote>

<footnote n="59">59 Published the 31 May 2014 by E. Forenza: « Après la réunion des candidats, une confirma- tion : l'@altraeuropa continue ! Nous avons une grande responsabilité : ne pas disperser le travail accompli ! », (traduction personnelle).</footnote>
s'agit plutôt de diffuser des informations autour des événements que d'instaurer des interactions. Ce qui rythme leur écriture est pour la majorité un évènement médiatique hors du microblogging.

Autour des jours du vote, la présence et la mise en scène de la candidate sur le microblogging a augmenté sensiblement paradoxalement grâce aux retweets plus qu'aux tweets mêmes. Déclarations, vidéos, photographies et slogans envahissent l'accoun de la candidate qui laisse ses «traces numériques<fnref n="60" />» avec une fréquence moyenne de 4 fois par jour. A noter que l'émission de tweets et retweets est relativement concentrée dans le temps, les tweets se suivent à intervalles variables de quelques minutes à quelques heures. L'échange est très intense pour ensuite se diluer dans le temps.

Forenza fait de l'autopromotion en publiant le bulletin de vote à employer le 24 et le 25 mai avec son nom déjà écrit et souligné. Tout est à empoigner pour la valorisation de soi : l'appui des amis qui parlent de la générosité de Forenza et même d'un membre proche de la famille (un frère ?) qui affiche une photographie d'un autre temps de la candidate, servent à construire le personnage médiatique.

Les internautes « participent» à la vie médiatique de Forenza qui tweete à ces followers depuis le Parlement européen, qui se réjouit pour les batailles qu'elle commence à mener, qui dévoile son « humanité », en se présentant dans la vie active et en affichant ses émotions et ses passions<fnref n="61" />. La stratégie de la subjectivité et de l'empathie font partie désormais d'une nouvelle façon de faire politique aujourd'hui et Forenza part d'elle-même pour témoigner des actualités de la sphère publique. L'expérience, l'être là qui normalement appartenaient à la dimension du privé, sont valorisés comme points de départ pour appréhender le réel<fnref n="62" />. La candidate implique l'internaute dans sa vie publique pendant la campagne électorale en rappelant des informations techniques sur les élections (lieu, débat,

<footnote n="60">60 B. Galinon –Mélénec & S. Zlitni, *Traces numériques*, CNRS, 2013.</footnote>

<footnote n="61">61 Pour l'importance de la composante passionnelle, nous renvoyons à A. J. Greimas & J. Fontanille, *Sémiotique de passions. Des états de choses aux états d'âme*, Paris, Ed. du Seuil, 1991 et aussi à J. Fontanille, *Soma & Séma : Figures du corps*, Paris, Maison-neuve & Larose, 2004. L'étude de la composante passionnelle et en particulier celle corporelle dans l'écriture, l'image et plus en général l'échange sur le microblogging Twitter reste encore une dimension à explorer.</footnote>

<footnote n="62">62 Il s'agit d'une nouvelle dimension du partage de la sphère publique et personnelle. A ce propos, nous renvoyons à A. Frame & G. Brachotte : « Les campagnes des compagnes : mise en scène de la vie publique et privée. La présence sur Twitter des compagnes des leaders politiques en France, en Grande-Bretagne et aux Etats-Unis », (sous la dir. de) S. Zlitni & F. Lieanard, *La communication électronique en questions*, Berne, Peter Lang, 2013, pp. 387-402.</footnote>
initiatives locales) et en cherchant de sensibiliser avec des slogans l'opinion publique sur certaines thématiques (oggi giornata mondiale contro l'omofobia, sta per arrivare il 25 maggio<fnref n="63" />) et en créant un actant collectif animé par la même passion (@romano_tano @altraeuropa grazie! Bravi tutti noi che ci crediamo e non ci arrendiamo mai!; sta per partire il corteo beni comuni, noi siamo qui per appoggiarli; qui sono stati toccati i nodi di fondo di questa campagna<fnref n="64" />).

La candidate exploite Twitter comme désormais est coutume : un outil pour réduire la distance entre citoyens et sphère publique. Comme le soutient J. L. Dader « Ainsi, bien que l'analyse politique ne soit pas rigoureuse, ni le débat politique de qualité, les individus se trouvent plus proches des affaires publiques, de telle sorte que la politique cesse d'être élitiste et ennuyeuse, exclusivité des classes dirigeantes au regard du peuple. L'info-entertaining télévisuel et de la presse à sensation avait déjà créé et mûri progressivement cet effet de la politique pop (Mazzoleni & Sfar-dini, 2009), mais Internet a contribué de façon exponentielle à son accroissement dans une dimension que les médias du passé, essentiellement unidirectionnels, ne pouvaient pas faciliter<fnref n="65" /> ». L'idée d'une « libre » circulation de la parole et d'un échange « directe » amène l'illusion d'une fausse proximité avec le candidat qui se représente d'abord comme un citoyen parmi d'autres.

### 4.7.1 Le- re-tweet de E. Forenza

Sur cette deuxième pratique, nous assistons concrètement à la publication d'un tweet d'une personne par un autre utilisateur. Il s'agit d'une rediffusion d'un contenu, jugé particulièrement pertinent à un moment donné. Le symbole RT suivi du pseudonyme de la personne qui a retweeté, caractérise cette pratique. Le contenu du message peut être renvoyé tel quel en ajoutant de la valeur au rédacteur du tweet ou il peut se compléter par un commentaire personnel du retweeteur, placé avant le symbole RT. Dans notre cas, Forenza n'écrit aucun commentaire dans le retweet pendant toute la campagne. Les autres supporteurs parlent d'elle mais toujours d'une manière directe mais la candidate emploie le retweet pour

<footnote n="63">63 (Aujourd'hui journée mondiale contre l'homophobie, le 25 mai va bientôt arriver), traduction personnelle.</footnote>

<footnote n="64">64 (@romano_tano @altraeuropa merci ! Bravo à nous tous qui continuons à croire et qui ne cédons jamais ! le cortège autour de biens publiques est en train de partir, nous sommes ici pour les soutenir ; ici nous avons touché les nœuds sensibles de cette campagne électorale), traduction personnelle.</footnote>

<footnote n="65">65 J. L. Dader, « La transformation de la politique sur internet : de la politique spectacle à la cyberdémocratie d'activisme citoyen », *Networks and Communication Studies*, NETCOM, vol. 26 (2012), n° 1-2 p. 18.</footnote>
informer et non pour s'exprimer. D'où toute la problématique d'usage du retweet qui en même temps accumulerait au moins deux fonctions en un seul medium : celle de diffusion des contenus médiatiques, de citation, de focalisateur d'attention sur une thématique et celle de mise en scène de soi, d'expression personnelle<fnref n="66" />. Le fait d'attirer l'attention sous-entend aussi une volonté de surligner un événement dans le but de l'emphatiser, de le remettre au centre pour pouvoir ensuite d'y rebondir. Nous ne pouvons pas oublier qu'une des fonctions de Twitter est justement la veille informationnelle qui s'opère de différentes façons : hashtags, moteur de recherche, mots-clés, etc.

Cette fonction de retweet est de plus en plus employée jusqu'à la fin de la campagne électorale. La majorité de retweets concernent directement ou indirectement la candidate. Il s'agit de messages de soutien en sa faveur, des compliments pour la victoire obtenue, des encouragements de la part d'autres votants, de collectivités et de partis. Les incitations à la candidate n'explicitent pas les raisons du soutien mais ressemblent à des marques personnelles d'estime et d'incitation. Les personnes qui ont porté Forenza ont laissé des tweets, retweetés ensuite par l'élue, comme « témoignage » de leur engagement. Nous passons d'un électorat potentiel à l'assurance que derrière le tweet nous retrouvons des personnes concrètes qui ont appuyé la candidate. En outre, laisser une trace évidente de sa propre énonciation incite d'autres followers à suivre et à encourager la candidate. L'appui à cette dernière se fait aussi grâce à la présence ferme de ces followers qui restent la meilleure preuve du bienfait de la postulante.

Encore, le retweet est employé d'une façon indirecte en tant que « rebond » autour des thématiques chère à Forenza. Il s'agit de citer d'autres déclarations des politiciens pour pouvoir rejaillir de ses propres propos, les développer, les remettre dans la sphère du blogging. Nous avons constaté des liens thématiques évidents entre les propos de Forenza et les contenus des retweets. Par exemple, le message de l'account "L'Antifascista": « Sta per partite il corteo beni comuni e

<footnote n="66">66 A ce propos je renvoie à la présentation de A. Frame & T. Kondrashova, « Exploring the dialogical dimension of political tweets : A qualitative analysis of Twitter style of UK candidates during the 2014 Eu Parliamentary Elections », communication présentée au meeting du 5-6 février 2015, université de Lorraine, Metz. Il est question dans cette communication d'opposer le tweet personnel-interactif marqué par la présence de majeur @ et RT à celui informationnel qui serait caractérisé par un nombre majeur de liens hypertextuels. Sur cette division, C. Thimm, J. Einsapchner, Dang-Ahn M., 2012, Twitter als Wahlkampfmedium, Publizistik, 57 (3), p. 293-313.</footnote>
noi siamo qui ad appoggiarli #primalepersone pic.twitter.com/PznQZsTxJe<fnref n="67" /> », a été repris par Forenza pour raconter sa présence à une manifestation autour de toute autre thématique. La mise en valeur de soi passe aussi par le fait de se montrer en plein engagement, dans les feux de l'action sur multiples terrains. Les évènements publics sont rattachés à la candidate et réinterprétés par son idéologie politique. Le contenu informatif d'un retweet fournit l'occasion pour une prise de parole en public qui marque la présence de la candidate. C'est le cas de ce retweet : « Garantire uno standard salariale e il reddito minimo di cittadinanza », suivi par quelques secondes après, « Verso Taranto, con @giakrussospena e @eleonoraforenza per "Tsipras chi?"<fnref n="68" />» (11/05/2014).

## 4.8 Le cas d'I. Adinolfi

La candidate a émis 442 tweets pendant les 4 semaines de recueil de données. Le double par rapport à la candidate précédente. Est-ce que la présence constante et continue sur Twitter permet d'afficher une stratégie communicationnelle plus représentative pour mener une campagne politique en ligne ? Il parait que oui.

D'abord, la candidate est présente avec un nombre de tweets majeurs par jour (une dizaine). Les échanges se font sur une fréquence très courte (quelques minutes) et avec des rebondissements autour de la même thématique. L'idée est de se concentrer sur un thème central de la journée et ensuite continuer à le nourrir pendant la longueur du jour. De la communication de la nouvelle « complète », on assiste à l'expression du point de vue du M5S qui transforme le contenu en « nouvelle virtuelle », centrée autour des déclarations, commentaires, polémiques, débats etc. Nous assistons aux discours autour d'un contenu qui est ensuite oublié pour passer à un autre argument. Les rebondissements médiatiques servent à alimenter les discussions et la présence de la candidate.

Les stratégies adoptées par Adinolfi sont de deux types : d'une part le retweet des nouvelles dont le M5S n'est peut-être pas le protagoniste mais où il veut exprimer en tant que parti ; de l'autre la rédaction constante de tweets qui manifestent l'implication de la candidate pour les causes du mouvement. A ce propos : « @m_ariano5stelle #campaniatour, dopo il diluvio...il sole e @AngeloTofalo ci

<footnote n="67">67 Publié par Forenza le 17 mai 2014. « Le défilé pour la protection des biens communs est en train de commencer et nous sommes ici pour l'appuyer #primalepersone pic. twitter.com/PznQZsTxJe », (traduction personnelle).</footnote>

<footnote n="68">68 « Garantir le minimum salarial et une redevance minimale pour la citoyenneté », « Vers Taranto avec @giakrussospena et eleonoraforenza pour « Tsipras qui » ? », traduction personnelle.</footnote>
parla del lavoro dei ragazzi del #m5s! http://t.co/VzjbvgGfd7 », « Domani tutti in Molise con il Campania tour<fnref n="69" /> ».

Bien évidemment, le style polémique, qui a caractérisé son principal candidat, Beppe Grillo, est présent à travers des tweets comme : « Pool trattativa smantellato, siamo indignati », « In scena il delitto perfetto, non consentitelo, solo rappresentanza massiccia di forze del cambiamento puo' impedirlo<fnref n="70" /> ».

Il ne manque pas de propagande pour le parti même comme « Siamo a Tremoli, seguiteci in diretta streaming qui http.. », « in Europa una scelta a cinque stelle », « Per il PD se non hai soldi non vali niente, il M5S è diverso, siamo una comunità <fnref n="71" /> », etc.

Nous constatons que la candidate cherche à exploiter toutes les possibilités et les variétés du médium en utilisant les différents niveaux du discours ; de la persuasion à la polémique, à l'emphase.

La présence de retweets (149) reste aussi pour cette candidate majoritaire ; ils sont suivis principalement par les commentaires de la part de la candidate. Malgré la fonction de retweet employée comme auparavant pour rediffuser l'information, Adinolfi commente les actualités par le biais de la coloration politique du M5S. Quelques retweets : « Riordino per il corpo dei #vvf.Ma i criteri seguiti sembrano sempre gli stessi:TAGLI!<fnref n="72" /> » (23/05/2014), ou « RT @MicFailla: @Isa_Adinolfi @frattademo avete letto le falsità del soporifero editoriale di Salfari? http...73 » (18/05/2014). Les faits divers de l'actualité servent à la candidate pour s'élever comme porte-parole et commentatrice des positions politiques du parti. Toutes les occasions sont exploitables pour montrer l'opinion contrecourant et dénonciatrice du M5S par rapport à la politique actuelle. Bien sûr la volonté « de crier fort » et d'assumer une position d'opposition dans tous les domaines politiques a fait un des succès de ce parti.

<footnote n="69">69 « Après le déluge, le soleil et @Angelo Tofalo nous parle du travail des jeunes... », « Demain tous au Molise pour le Campania tour », traduction personnelle.</footnote>

<footnote n="70">70 « Tractations pour le Pool sont tombées, nous sommes indignés », « Nous ne pouvons pas assister à ce délit parfait, seulement une importante présence des forces du changement peut empêcher tout ça », traduction personnelle.</footnote>

<footnote n="71">71 « Nous sommes à Tremoli, suivez- nous en direct streaming ici http.. », « En Europe un choix à cinq étoiles », « pour le PD si tu n'as pas d'argent tu n'as aucune valeur, pour le M5S c'est différent, nous sommes une communauté », traduction personnelle.</footnote>

<footnote n="72">72 « Rangement pour le corps desvvf. Mais les critères suivis sont toujours les mêmes : Diminution d'argent », traduction personnelle.</footnote>

<footnote n="73">73 « Entretemps avez-vous lu les faussetés de l'ennuyeux et soporifique éditorial de Scalfari ? », traduction personnelle.</footnote>