www.ssoar.info

From Data to Discourse: How Communicating Civic
Data Can Provide a Participatory Structure for
Sustainable Cities and Communities
Shibuya, Yuya; Hamm, Andrea; Raetzsch, Christoph
Veröffentlichungsversion / Published Version
Konferenzbeitrag / conference paper

Empfohlene Zitierung / Suggested Citation:
Shibuya, Y., Hamm, A., & Raetzsch, C. (2021). From Data to Discourse: How Communicating Civic Data Can Provide
a Participatory Structure for Sustainable Cities and Communities. In Proceedings of the 27nd ISDRS '21. Östersund:Mid Sweden University. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-74871-6

Nutzungsbedingungen:Dieser Text wird unter einer CC BY Lizenz (Namensnennung) zur
Verfügung gestellt. Nähere Auskünfte zu den CC-Lizenzen finden
Sie hier:https://creativecommons.org/licenses/by/4.0/deed.deTerms of use:
This document is made available under a CC BY Licence(Attribution). For more Information see:https://creativecommons.org/licenses/by/4.0

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

From Data to Discourse
How Communicating Civic Data Can Provide a Participatory Structure for Sustainable Cities andCommunities
Yuya Shibuya1, Andrea Hamm2, Christoph Raetzsch3
1

The University of Tokyo, yuya-shibuya@iii.u-tokyo.ac.jp

2

Weizenbaum Institute / Technical University Berlin, andrea.hamm@tu-berlin.de

3

Aarhus University, Department of Media and Journalism Studies, craetzsch@cc.au.dk

Abstract
This study explores how Civil Society Organizations (CSOs) have leveraged civic data to facilitate
democratic participatory structure for sustainability transitions around the case of bicycle counters in three
US cities over a ten-year period (Seattle, San Francisco, Portland). We identified that CSOs have played
crucial roles in public discourse by (1) sustaining long-term public issues through shaping affective as wellas analytical discourses and (2) fostering citizens’ sense of ownership and contributions toward sensor
devices and the data they generate by contextualizing them through local civic life as well as connecting
issues to actors in other cities.
Keywords: Civil Society Organizations, Civic Data, Bicycle counter, Participatory structures, Sustainable
Development Goals

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

1. Introduction

Civil Society Organizations (CSOs) is an umbrella term that encompasses different types of networks andinstitutions ranging from transnational non-governmental organizations to small community groups (United
Nations, 2018, para 20). CSOs enable democratic participation and are regarded as central for achieving
the UN’s Sustainable Development Goals (SDGs). Despite their recognized importance, conventional
forms of CSOs have struggled to recruit supporters especially from younger generations (Wells, 2015).
New types of CSOs address citizens through performative and quotidian media practices (Foellmer et al.,2018; Mattoni, 2016) creating forms of political activism as “connective action” (Bennett and Segerberg,2012). The present study analyzes the roles that these new types of CSOs have in sustainability transition,
looking specifically into bicycle counters as sensor devices that are visible in public spaces and that become“communicative objects” (Raetzsch and Brynskov, 2018) in public online discourses.
This exploratory case study makes a contribution to understanding new democratic participatory structuresin cities and communities (SDG 11.3.2) in the context of CSOs, citizen-centered innovation, and public
contestation through social media. We analyze how electronic bicycle counters are becoming accepted andowned by communities in the transition to sustainable cities where the modal share of cycling is required
to increase to reduce carbon emissions from car traffic. Such sensor devices generate “civic data” (Hammet al., 2021) by monitoring citizens’ movement but also by generating crowd-sourced, collective
representations of change in the city itself that citizens can contribute to. To make civic data actionable,
however, data alone is insufficient (Assad et al., 2017; Chen and Aitamurto, 2019; Foth and Brynskov,
2016; Raetzsch et al., 2019; Foth et al. 2011). We want to understand how civic data in the case of bicycle
counters are made actionable in public discourses and which roles CSOs play in this process.
Bicycle sensors are visible interventions in urban space, their data represents and monitors diffuse patternsof collective mobility. Through social media, citizens are likewise referencing, challenging, or embedding
their own experiences into new forms of understanding change in the city. These overlapping processes oftechnological intervention and cultural contestation exhibit a slow and rather inconspicuous process of
infrastructuring, where different actors circulate different kinds of “communicative objects” (Raetzsch andBrynskov, 2018), highlighting the processes of negotiating and contesting individual and collective
meanings of technical infrastructures. By drawing on longitudinal as well as case-based data collections,discourse, and network analysis of social media data, we retrace how the communicative object of thebicycle counter triggers community-oriented perceptions of sustainability transitions around the subject of
cycling in the city.
The research question of this study is:27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

RQ: How have CSOs leveraged communicative objects to facilitate democratic participatory
structures in cities around bicycle counters in public spaces?
The study will explore how data generated by the interaction of citizens and bicycle counters becomes acommunicative object across stakeholder groups, highlighting the importance of CSOs to shape, moderate
and influence such public discourses. In this exploratory mixed-method study, we analyze English-language
discourses on Twitter and Facebook around bicycle counters in three US-American cities, focusing on three
CSOs in particular. The study makes two core contributions to understand the roles of CSOs to shapeparticipatory structures and make civic data actionable for sustainable cities and communities:
1. CSOs play a significant role in sustaining long-term public issues such as the safety of cycling in
the city through affective as well as analytic discourses based on data collected by bicycle counters.
2. CSOs contribute to citizens’ sense of ownership of sustainability transitions through enabling andeliciting the circulation of communicative objects, fostering a collective process where the impactof civic data is contextualized in local civic life.

This paper is organized as follows: We first review literature on CSOs’ changing use of digital media andthe role of civic data in Section 2. We then introduce our data collection, case selection, and methodology
in Section 3. In Section 4, we summarize our findings. Then, we discuss the case studies and point out the
CSOs’ roles in sustainability transitions in Section 5. In the conclusion, we call for a central

acknowledgment of CSOs as anchors of civic engagement in networked publics, arguing for the need for
democratic participatory structures in the use of civic data for fostering sustainability transitions.
2.

Literature Review

2.1 Civil Society Organizations, Connective Action, and Digital Media
Recent social movements such as the Occupy protests in the United States, have created much attention
toward the roles of social media as a participatory structure and mobilizing people. As Wells (2015) pointed
out, civic participation in the context of digitally-enabled social movements, contributes to the decline ofactivity in institutional CSOs. Communication is essential but often theoretically underdeveloped toaccount for the disaffection from politics especially among younger citizens and its link to concrete actions(Kim et al., 2010). Bennett and Segerberg (2012) emphasized that communication itself becomes theorganizational structure of the movement. Compared to traditional CSOs these emerging new forms of“connective action” loosely offer variegated ways of public engagement through individual sharing ofpolitical ideas, memes, and information on digital media (Bennett and Segerberg, 2012). Similarly, Diani(2015) argued that networks are not just precursors or building blocks of collective action: they are in27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

themselves organizational structures that engage individuals beyond formalized demands for membershipin organizations.
In these new activist contexts, social media play a central role in enabling variegated types of sporadic aswell as long-term participation, creating opportunities for mobilization in key instances of a movement aswell as forging a joint community spirit from individuals interventions and experiences, a new form of“cloud protesting” (Milan 2015). These developments shift the role of CSOs from being a single
institutional and representative actor in political discourses to a networked logic that creates the “glue thatbinds public and private activity together” (World Economic Forum, 2013, p.5). CSOs and associations ofindividuals act as a “facilitator in loosely linked public engagement networks” (Bennett and Segerberg,
2012, p.758) of democratic participation (United Nations, 2018; Karph 2015). The creative use of social
media and digital communication formats by CSOs is well recognized as crucial for developing inclusive
discourses and narratives around sustainability transitions across different stakeholder groups throughexperimentation and interventionist practices rather than formalized processes of political participation(Hamm et al., 2021; Köhler et al. 2019; Sengers et al. 2019; Brynskov et al. 2018; von Wirth et al. 2018;

Werbeloff et al. 2016).
Many CSOs struggle to transform their traditional participatory structure based on formal membership.
New kinds of CSOs have successfully adopted digitally enabled communication modes to leverage a wider
participatory potential from their supporters and followers (Karph 2017). Prominent examples of theseparticipatory modes employed by CSOs include publicizing social issues (Bruns and Burgess, 2011),
increasing public discourse visibility (Andrews and Caren, 2010), linking diverse actors (Wonneberger etal., 2020), and mobilizing public attention (Wang et al., 2016). Karpf (2017) emphasizes the need for CSOs
to listen to these articulations, arguing that “analytic activism” leverages affordances of digital technologies

to fashion new strategic interventions in the political arena. Protest movements filter and moderate bothinternal and external communication processes where “mediation opportunity structures” are exploited togive voice and visibility to issues of public concern (Cammaerts 2012). CSOs and dispersed social
movements are then challenged to both observe, facilitate, articulate, and channel diverse communication

streams through new kinds of distributed media and protest practices that link to personalized habits andcommunication routines of their supporters and followers (Mattoni 2020).
In the broader discourse on sustainability transitions, we conceptualize social media communication as ademocratic participatory structure for emerging topics in which CSOs play a central role. While being awareof the various shortcomings of social media technologies, e.g. digital divide, platform logics, algorithmic
content amplification, these platforms also offer affordances for CSOs to build up and sustain networks ofengaged citizens.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

2.2 Civic data
Civic data is commonly understood as data that is both captured and owned by the citizens as a form of thecrowd-sourced, open data asset. Its aim is to provide citizens with the means and knowledge to act uponpressing local issues through evidence-based data collections, e.g., on air pollution or radiation (Hamm etal., 2021). The public distribution of civic data needs to be complemented with broader communication
strategies that include citizens’ shared opinions, emotions, and experiences relating to pressing social issues(Brynskov et al., 2018; Hamm et al., 2021). Collaborative knowledge creation and social change here
coalesce with wider public discourses through deliberation in multiple communicative spaces, e.g. in local
urban spaces, in the news media, and on social media. Civic data is connected to what Wells (2015) calls“civic information” that is conceptualized as “the continuous flow of facts, opinions, and ideas that help
citizens understand matters of potentially public concern and identify opportunities for action” (p.7). While
civic data refers to data assets created by and for activists and citizens, civic information refers to theprocesses of making sense of data and leveraging the impact of big data for social change (Cuquet andFensel, 2018; cf. Zins 2007).
To make civic data actionable for various actors, however, there is a need to design and implement
interfaces that make data accessible to the broader public (Assad et al., 2017; Raetzsch et al., 2019), a
structure to appropriate their city to take action for change (Chen and Aitamurto, 2019; Foth and Brynskov,
2016; Hamm et al., 2021) and to be able to institutionalize and grow communities of socio-technical practicein symbiosis with other systems and institutions (Foth and Brynskov, 2016; Gordon and Mihailidis, 2016).
In detail, Foth and Brynskov (2016) underscored the importance of civic engagement in a way that allows
a multiplicity of voices to be listened to, instead of merely using the pool of data for specific purposes.
Finding information that matters requires contextualization based on the specific individual needs of actors.
Successful deployments of civic data have been backed up by the process of co-developing a novel
technology to solve a target problem by mediating an entire network of social practices and galvanize
multiple organizations and user groups (Liu et al., 2019). In addition, social media has become an important
structure to generate and disseminate citizen information in local communities and CSOs have assumed
important roles as communicators and information producers (Thorson et al., 2020). Meanwhile, generatinglarge amounts of civic data (i.e., civic data overload) has created challenges in processing the data, such as
which voices are to be heard and considered by authorities (Chen and Aitamurto, 2019). Thus, we are now

more in demand for what research on Digital Civics call for: exploring the potentials of digital technologies“to reconfigure power relations between citizens, communities and the state” (Vlachokyriakos et al, 2016,p.1096).

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

3. Methodology

3.1 Data collection and Case selection
In this study, we analyze bicycle counters as prominent subjects in English-language online discourse,
principally on Twitter and Facebook. The corpus of social media data was constructed through thefollowing two stages. First, we compiled a data set from Twitter and Facebook Pages (excluding Retweets)

containing the words “bicycle/cycling/bike counter(s)” for the past 10 years. Twitter data were gathered
through the Twitter API with an academic account while Facebook Pages’ posts were gathered throughCrowdTangle API with an academic account. We found the oldest available posts in CrowdTangle was inFebruary 2011. Thus Facebook Pages’ data in our corpus covers the data from February 2011 to December
2020 (119 months) while Twitter data covers the tweets from January 2011 to December 2020 (120months). Due to search queries posted in English, the resulting data set showed a strong majority of activity
in US-American cities, the three most prominent ones being Seattle, San Francisco, and Portland. These
three cities were identified based on the number of posts that contain location information. We decided tofocus on these cities to illustrate the dynamics between civic data, citizens, and CSOs while fully
acknowledging that a future study could contain a more targeted search for cities in which bicycle counterswere prominently discussed (e.g. Aarhus/Denmark, Amsterdam/Netherlands, Berlin/Germany).
Secondly, we found the most commonly used hashtags related to bicycles in local contexts in the corpus,
collected additional Twitter and Facebook data for the past 10 years with those location-based hashtags,
and added them to the corpus. The hashtags for the additional data collection are #SEAbike(s), used in
Seattle, #SFbike(s) and #bikeSF, used in San Francisco, and #pdxbike(s) (pdx is a nickname of Portland),used in Portland (all hashtags were case insensitive). In total, our corpus consists of 34,037 Tweets and 448
Facebook posts. In addition, for quantitative network analysis (described later in Subsection 3.2), we further
collected retweets and replies to the Tweets in our corpus through Twitter API (we did not conduct thisfurther data collection on Facebook Pages’ data because CrowdTangle API does not allow us to do so).
These additional data of retweets and replies (53,540 Tweets) are only used for network analysis, not in
qualitative in-depth analysis. In addition, for qualitative in-depth analysis, we additionally collected online

materials, including reports, media news articles, and press releases, through keyword news article searches
and tracking social media data references.
With this corpus, we extracted the accounts of CSOs that have been the most actively communicating in
Seattle, San Francisco, and Portland. As a result, we selected the following three CSO cases in three US

cities:27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021-

Case Seattle: Cascade Bicycle Club (WA) is a statewide bicycling nonprofit organization locatedin Seattle. Founded in 1970, it has continuously advocated for the safety of cyclists. In Seattle, thefirst bicycle counter was installed in 2012.

-

Case San Francisco: SF Bike Coalition (CA) is also one of the oldest bicycle advocacy groups
founded in 1971, which has promoted bicycling for everyday transportation (SF Bicycle Coalition,n.d.). San Francisco first installed a bicycle counter in the city in 2013 (San Francisco Municipal
Transportation Agency, 2013).

-

Case Portland: BikePortland.org (OR): BikePortland.org was founded in 2015 as a civic media
organization. Portland installed the first-in-the-U.S. bicycle counter in 2012 (Portland Bureau ofTransportation, 2013).

Cascade Bicycle Club (Seattle) and SF Bike Coalition (San Francisco) have long histories of cycling
advocacy while BikePortland.org is a relatively new organization founded after the rise of social media.
We analyze the corpus of social media posts as a whole to capture overall trends of discourses about bicycle

counters. We then explore bicycle counters in the case studies of Seattle, San Francisco, and Portland ascommunicative objects of social media discourse.

3.2 Data Analysis
In this study, we apply mixed methods to explore longitudinal data (2011-2020) on the bicycle counter
discourse in Twitter and Facebook. From this large corpus, we focus especially on three cases, which weanalyze by social network analysis and critical discourse analysis of linked content outside social media.
For conducting the social network analysis, we construct retweet and/or reply networks of users in theTwitter data enriched by an additional data collection described in Section 3.1. Our network analysis wasdone with the Python package NetworkX. We created a network graph where each node represents a Twitter
account colored according to city-related hashtags, i.e. Seattle related hashtag (#SEAbike(s)) in green,
Portland related hashtag (#PDXbike(s)) in orange, and San Francisco related hashtag (#SFbike(s) and#bikeSF) in light blue. Each edge represents a retweet and/or reply connection between accounts. We apply
this network analysis to accounts in all three of the selected cases.
For qualitatively examining the corpus, we applied critical discourse analysis (CDA) that has been
traditionally used to uncover discourses that maintain power relations of existing elites and institutions(Willig, 2014) and is more recently used to study social media (Bouvier and Machin, 2018) and public
discourses around new technologies (Hamm and Lin, 2018). We here apply CDA to understand how civic

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

data is used to initiate discourses that negotiate sustainability transitions by CSOs, potentially shifting
power hierarchies between policymakers, citizens, CSOs, and other stakeholders.
4.

Findings

4.1 Patterns of public discourse: From contested innovation to accepted infrastructure
Our corpus consists of 34,358 posts (34,037 Tweets and 448 Facebook Page posts) in the past ten years.
Among them, the majority of posts were created by users located in the United States while many posts, inparticular Tweets, were by users who do not share location information. In Figure 1, the monthly numberof posts in our corpus is plotted over the period from January 2011 to December 2020. Yellow bars represent
the posts mentioning the keyword “bicycle/bike/cycling counter(s)” and grey bars show the number of posts
with hashtags (#pdxbike(s), #sfbike(s), #bikesf, and #seabike(s), if a post has both bicycle counter keyword
and hashtag, the post is counted in yellow bars) in our corpus. Networking through the use of hashtags has
been more active on Twitter than on Facebook, a defining feature of user practices on the platform. Overthe past ten years, the highest numbers of posts per month typically occur when bicycle counters were set

up in cities. For example, the number of posts was highest in August 2012 when the city of Portland installed
its bicycle counter (584 posts on Twitter and 24 posts on Facebook). In Facebook Pages, the second-highest
number of posts was observed in December 2016 when the city of Santa Monica, California, installed its
first bicycle counter (17 posts). Similarly, the highest number of comments, replies, and shares (retweets)

occurred at times when the first bicycle counter installations happened: In Facebook, the highest numberof interactions occurred when the city of Victoria in Canada installed its first bicycle counters in August
2019, followed by Carmel, Indiana in May 2015. On Twitter, the highest activity occurred when Santa
Monica (Dec 2016) and San Francisco (May 2016) installed bicycle counters.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Figure 1. Monthly number of Tweets (top) and Facebook Pages’ posts (bottom). The yellow bars
represent monthly numbers of posts containing the keywords “bicycle/bike/cycling counter(s)” and greybars represent monthly numbers of posts containing hashtags (#pdxbike(s), #sfbike(s), #bikesf, and#seabike(s). Orange broken lines depict summed numbers of reactions (replies, comments, and shares)that posts in the month gained. Bars contain only original posts (i.e., no replies, comments, shares,
retweets, etc.), the orange line quantifies all reactions to the original posts.). Both in Facebook andTwitter, one of the biggest peaks of communication occurred in August 2018 when the first-US bicycle
counter was installed in Portland (584 posts on Twitter and 24 posts on Facebook). Similarly, the numberof interactions that posts had, i.e., numbers of comments, replies, and shares (retweet), was the mostintense when bicycle counters were installed both in Twitter and Facebook posts.

There were steady numbers of posts in each month since 2011 on Twitter. Since around 2016 yet the total
number of posts on Twitter has slowly declined. In particular, the number of posts that include the keywords“bicycle/bike/cycling counter(s)” have decreased since around 2012 and there were only a few posts

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

containing the keywords after 2017. This might reflect the process of bicycle counters becoming accepted
as quotidian elements of urban infrastructures. In addition, new sources of bicycle movement data (e.g.
through tracking apps) have complemented stationary counting systems over the last years. In Portland, forinstance, the city started to incorporate other types of data that capture bicycle usages and travel patterns,
such as purchasing the data from a mobile app company (Maus 2014; Portland Bureau of Transportation,2018).
Overall, the general pattern of discourse on bicycle counters shows three distinct phases and subjects:
installation of bicycle counters as a public event, the process of crowd-sourced data collection, and sharing
collective civic data in support of mobility transitions.

4.1.1 Discourses on installing bicycle counters
Throughout the 10-year period of bicycle counter discourse, the installation phase of bicycle counters in
the respective cities generated the majority of articulations on social media. The installations of new bicycle
counters are typically met with both favorable and unfavorable reactions. Positive reactions are based on
excitement about the new means to acquire data and the new experiences of being counted, e.g., “Great toshow car drives how many bike journeys are taken!,” “could be useful to argue for more bike lanes,” and“Excited I make my rides count!” The majority of negative reactions refer to using tax money on bicycle
counters, such as “70k would be better used repairing potholes and adding raised didewalks (sic!)”, “How

about spend money on helping housing and cars than bike lanes?! Not every soul can bike!” Such posts
also stimulate citizens elsewhere to demand bicycle counters for their cities as well. Comments such as“why hasn’t the city installed a single bike counter?,” or “OK, we are jealous of Portland’s bike counter.
Where would you put a bike counter in the East Bay?,” or “Is Portland’s bike counter a solution for the

New York City’s bike ridership debate??” show the pioneering role of the first cities.
4.1.2 Discourses on the crowd-sourced generation of data
Alongside the collection of civic data on the counters themselves, we see several types of discourse

emerging where the counters themselves are becoming communicative objects. One of the most observed
types is sharing personalized experiences of being counted. Citizens excitedly document their experiencesof being registered by counters through posting images and videos. There are also posts sharing how thepresence of counters nudged citizens to use bicycles (more). After counters have become normal andaccepted as part of the urban infrastructure, celebrating how bicycle counters hit 1 million cyclists recorded
in one year also elicited many positive reactions from citizens. Compared to the installation phase, thenumber of critical posts about bicycle counters decreases as people contribute to generating data. Only a27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

few posts criticize the accuracy of data counts, the locations of bicycle counters at highly-frequented roads,
or public spending on bicycle counters.
4.1.3 Discourses on interpreting a collective civic data asset
The most prominent yet unique type of discourse in our corpus is about analyzing and interpreting bicycle
counter data as a collective civic data asset. The generated civic (and open) data allows anyone (who has
the skills and knowledge to do so) to analyze and interpret the data to make sense of bicycles in their cities
and construct their own ideas, opinions, and plans for actions. Figures or tables of data eschew an analyticalperspective on cyclists’ mobility. Many posts show how bicycle use has grown over the years, e.g., bycomparing annual numbers of bicycle counts, peaks of commuting hours, or seasonal differences. As moredata is accumulated, various types of analyzes contribute to changing people’s perceptions of the issue aswell as making sense of a collective civic data asset. For example, during the COVID-19 crisis, civic data
accumulated through bicycle counters in the US show steep increases in cycling (e.g., a tweet with multiple
colored figures showing the analytical results: “How has COVID-19 affected biking in your city? We’retaking a look at Urban Cycling Patterns During a Pandemic: Seattle Bike Counter Analysis, in our mostrecent blog. Read more here: [url]”). One of these analytical results describing changes in bicycle use
across the United States was shared by the international newspaper The Guardian resulted in more responses
online.

4.2 Making sense of civic data: Network structures and discourse opportunities
In this section, we turn our attention to the role of CSOs’ in creating and shaping civic data as acommunicative object of public discourse. We first present social network analysis results on each case in
subsection 4.2.1 and then present the findings of the CDA in subsection 4.2.2.
4.2.1 Networks around central activist accounts
To understand how CSOs have positioned themselves in their respective communities, we calculated
Twitter network graphs of the cases based on hashtags. In Figure 2, each CSO in the three cities is shownin the purple nodes while other users in the networks are shown in uniform colors, i.e., green, blue, andorange respectively. The network graph shows how local online discourses of the three cities have evolved
and become connected with each other and with different cities.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Figure 2. Twitter networks for each CSO in the selected case studies. Each node represents an account
while each edge represents a reply or retweet between accounts. The node sizes represent the frequencies
of being retweeted and replied to.

Table 1 summarizes basic indicators of each case’s network structure. Case Seattle shows very closelyaligned edges, i.e. a focused network of accounts, compared to a more thinly and widely distributed networkof edges and accounts in Case San Francisco and Case Portland. Regarding degree centrality (i.e., the countof how many social connections each node has), all CSOs are positioned equally central in their hashtag

networks. Interestingly, there is a great discrepancy between the cases regarding betweenness centrality(i.e., capturing the amount of influence a node has over the flow of information in a network): For Case B(SF bike coalition in San Francisco) betweenness centrality is comparatively higher, indicating that they
serve as an important broker between otherwise rather loosely coupled actors and networks.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Table 1. Indicators of network graph (Figure 2)(i) Density of network ofhashtags(ii) Degree centrality of CSO
account(iii) Betweenness centrality of
CSO accountCase Seattle

0.012

0.056

0.027

Case San Francisco

0.002

0.051

0.240

Case Portland

0.003

0.040

0.067

Note:
(i) Density of network is calculated separately on each case’s sub-graph (#SEAbike(s), #bikSF/sfbike(s), and #pdxbike(s)𝑚respectively). 𝐷𝑒𝑛𝑠𝑖𝑡𝑦 = 𝑛(𝑛−1)2 where m is total edges and n is total nodes in a sub-graph. A higher score reflects the sub-graphis more dense, meaning more connections between actors exist compared to how many connections between actors are
possible.
(ii) Degree centrality is simply a count of how many social connections each node has. Higher values mean that the node ismore central in the graph.
(iii) Betweenness centrality captures the amount of influence a node has over the flow of information in a graph. Higher scoresindicate a node works as a bridge in the graph.

4.2.2. Experiences of Data: From personal encounters to long-term visions
CSOs’ roles in facilitating sharing of personal experiences
After the installation of bicycle counters, the majority of posts in our corpus were about citizens sharing

their experience of bicycle counters and being counted by them. These posts generally contain the
excitement and positive emotions with self-portrait photos of them with a bicycle counter. Those posts
include, for example, “I’ve been making a point of going over the bike counter whenever I can. Sorta feels
like voting..several times a day.” and “Was secretly cheering every time we hit a bike counter today on thebicycle track.” The bicycle counter experience narratives spread into networks and it even nudged others
to experience the bicycle counting as well e.g., “[...] I wanted to be counted!” CSOs refrained fromadvocacy and subjective opinions when citizens shared their personal experiences with bicycle counters.
Rather, they acted as an information provider by posting new counters’ information and sharing thecounters’ cycling data (e.g., posts with the figure showing the increase of bicycle numbers in the city, suchas “Another record! Yesterday, 5,066 bicyclists crossed the Seattle Bike Counter on the Fremont Bridge!”(Case Seattle). In Case San Francisco the CSO nudged people to experience bicycle counters by posting,for example, “CONTEST: Guess how many bikes the new Market Street Bike Counter will count on Bike toWork Day. Closest to the actual number wins a free pro tuneup bicycle.” These types of posts seek toconnect individuals’ experiences to collective and visible action on behalf of cycling in the city.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

CSOs’ roles in generating and disseminating data-driven discourse

Diverse communications containing bicycle counter data become part of CSOs communication, forming ananalytical discourse aside from engaging citizens. Analytical discourse contextualizes civic data in a city’ssustainability transition. Analytical discourse can be provided by anyone (citizens, data scientists, CSOs,
or authorities) both inside and outside of the networks. For example, Case Portland (BikePortland.org) as a
civic media organization, has provided numerous bicycle-related articles. These articles include basic
patterns of bicycle usages in a month or year and increasing bicycle usages over time. As more data is
accumulated, more types of analyzes can be done to make the local context understandable to citizens
through data. For example, Cascade Bicycle Club (Case Seattle) initiated a discourse about the economic
benefit of bicycle counters in local areas to support business opportunities. Other examples of analytical
discourse are shown in Figure 3.
CSOs sometimes comment back to posts within the hashtag networks to address the potentials and meaningsof bicycle counters in their cities, e.g., “Collecting data to improve understanding of biking, will affectfuture policy” (Case Seattle). Case San Francisco (SF bicycle coalition) pointed to the challenges of equity
regarding who gets counted by sharing their own article about new counting installations in less central
districts: “Real talk: [San Francisco Municipal Transportation Agency]’s doing an increasingly strong job
at making sure that *everyone* who bikes gets counted. [url]” (Case San Francisco).

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Figure 3. Example posts of analytical discourse related to bicycle counters. The presentation of graphs
allows users to understand and interact with bicycle counter data as a communicative object. The posts(a), (b), and (c) are example Facebook posts by the CSOs while (d) and (e) are Tweets from other users in
the network.

CSOs’ role in connecting citizens to a shared vision of sustainable mobility
CSOs have also used hashtags to mobilize citizens for a joint vision of sustainable mobility. For example,
Cascade Bicycle Club (Case Seattle) raised awareness of the city’s delay in building its planned bikeinfrastructure, e.g., “Build a #BasicBikeNetwork now. #SeaBikes.” They coordinated on-ground meetings
at Seattle City Hall by tweeting: “Join us tomorrow to send a resounding message to City Council:#wecantwait for the #BasicBikeNetwork. [url] #seabikes” (Case Seattle). Through collaborations withother CSOs and citizens, this movement achieved that the plans of the Basic Bike Network were started by2019 (Seattle Neighborhood Greenways, n.d.).
While hashtags have been mainly used to connect local actors, CSOs have also employed hashtags toconnect individual communications that go across geographical boundaries. The hashtag #VisionZero is a

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

recent example. It is used to call for a framework to eliminate all traffic fatalities and severe injuries while
increasing safe, healthy, equitable mobility for all (Vision zero network, n.d.). For example, Cascade
Bicycle Club (Case Seattle) called for participation in this movement by posting:“We need action on #VisionZero now. While people walking or biking are involved in 5% of crashes
in Bellevue, we suffer 43% of injuries and fatalities. Join us at 6:30pm Thursday 12/12 at City Hall
to tell leaders we can’t wait for safe streets [url]” (Case Seattle)
SF bicycle coalition also tweeted with the hashtag, such as: “Show City leaders that inaction is
unacceptable. #VisionZero meeting today at 2pm. [url]” (Case San Francisco), echoed by similar calls foraction from Portland. These examples illustrate that the CSOs use loosely connected networks to mobilize
citizens and policymakers to take actions for sustainable mobility in their cities. The common use of thehashtag #VisionZero also supports our findings from the network analysis (see Figure 2) that CSOs fromdifferent cities connect with each other via social media to support common goals.
5.

Discussion

CSOs were found to have a strong role in making civic data actionable and relatable for citizens in several
ways. In their social media communication, this role can be found in two dimensions that facilitate
democratic participatory structures outside the domain of formalized political deliberation through activist
interventions and community-focused outreach. In particular, CSOs were found to offer both affective andanalytical ways in which overarching socio-political issues can be addressed from a data perspective and acitizen perspective (5.1). They also facilitate a long-term public negotiation over crowd-sourced data as an
asset that serves their communities in sustainability transitions and their pledge for safe cycling (5.2).

5.1 CSOs initiate affective and analytical discourses around civic data
The time of installing a bicycle counter typically coincides with a surge in social media activity, allowing
numerous citizens to voice their approving or dismissive opinions on these innovations. Papacharissi (2016)

described social media as generating a form of “affective publics,” understood as “networked publics thatare mobilized and connected, identified, and potentially disconnected through expressions of sentiment” (p.
311). Bicycle-counter discourses around civic data show that affective publics typically produce
disruptions/interruptions of dominant political narratives by presenting underrepresented viewpoints andmaking a rather abstract sensor an object of affective (positive or negative) investment. CSOs here connect
dispersed articulations around common concerns while seeking to articulate and promote a shared,
collective vision. Once civic data through bicycle counters becomes available, CSOs initiate discourses

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

based on the data itself and call for participation. Apart from effective identification through personal
experiences, CSOs shape analytical discourses with direct implications for policymakers. Civic data thenserves as evidence for a changing mobility paradigm allowing different forms of affective connection, newvisibility, and ownership. We observed that CSOs provide opportunities for affective identification while
also offering analytical discourses based on civic data. Affective identification with the issue (cycling
safety) and analytical discourses to endow the issue with public relevance (through civic data) contributeto the central role of CSOs as political actors.

5.2 CSOs enable ownership of civic data as citizens’ data

Bicycle counters have matured as a unique form of cities’ infrastructure as they gain acceptance among thewider public. Compared to citizen sensors installed in a bottom-up way (Hamm et al., 2021), bicycle
counters are mostly installed by cities in a top-down fashion. Yet, bicycle counters in our case studies
produce civic data as citizens gain a sense of ownership toward the counters and a feeling of contributing

to the generation of data. By sharing their personal experiences of being counted, reporting issues ofmalfunctions, and expressing pride in their city’s move to place counters, users on social media contributeto a sense of community and ownership on various levels of involvement. For example, one of the most
liked Tweets (>150) in our corpus was about a bicycle counter being protected during road repair works:“NOT ONLY did [account of the city’s department of transportation] pave a temporary detour sothat the 520 multi-use trail could still be used during construction, but they ALSO moved the bikecounter so it could still be used too!”
Similarly, some posts show forms of civic pride to see bicycle counters in cities (e.g., “I think my favourite

part of the southernmost section of the 1st street cycle track is the bike counter.”, “Never noticed thisCambridge “bike counter” before. So Cambridge.” or “More scenes to love in #bikefriendly #SantaMonica:
bike counter [...]”). These articulations on being counted and creating data make cycling more visible toauthorities and also car drivers, who command most of the space in public road infrastructure. It facilitatesa process of generating evidence that underscores a sustainability transition in mobility that is already wellunderway. In addition, through dialogue on social media, civic data is interpreted through a range of“epistemic voices” (Elfin 2008 quoted in Foth and Brynskov, 2016) as people are making sense of the datain their everyday lives. In contrast to legacy CSOs, we saw that the selected CSOs have used the dynamics
of circulation of communicative objects on social media to develop and sustain a democratic participation
structure that “pervades across all touch points of civic life.” (Asad et al., 2017, p. 2296). Coordinating andsustaining long-term discourses around bicycle counters through social media creates opportunities for27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

citizens to participate at various levels – from posting just one image to organizing a bike rally. CSOs here
act as anchors for individuals in fragmented networks to overcome the algorithm-based biases of social
media filtering (Chen and Aitamurto, 2019).
6.

Conclusion

This study analyzes the role of communication for situating civic data in cities and communities in thecontext of a democratic participatory structure (SDG 11.3.2). We explored prominent cases of bicycle
counters in the United States generating civic data as communicative objects of affective investment by
citizens that make data actionable for systemic sustainability transitions. Citizens and CSOs togetherorganize connective action, shaping a public discussion and offering incentives for participation. CSOs

sustain long-term networking by fostering a sense of ownership by contextualizing civic data in local civic
life as well as trans-local networks and policy. Despite the limitations of considering only social media datafrom US-based accounts, the study provides important contributions to understanding the challenges andopportunities for CSOs in using social media as a prime site of public negotiation of pressing social issues.

Advancing SDG 11.3 in the direction of democratic participatory structures around urban innovation will
require developing democratic processes for networked public interventions that bring together dispersed
but committed individual actors and networks around a shared vision of sustainability, urban mobility, andsafety.

From a democratic point of view, it is problematic that current developments have led to the use of nonaccessible mobility data for counting bicycles, e.g. in the form of phone tracking or similar apps. Promoting
civic data acquisition and widespread use will require governance structures where data generation andownership are negotiated in a democratic participatory process in order to make such data actionable anduseful for a range of different stakeholders–public and private ones. Relaying such democratic processes tothe domain of social media, as this study has shown, can be only a first step towards equitable and inclusive
data governance. As sustainability transitions depend on cross-sector collaborations, CSOs become more
important for dispersed and networked publics to channel very heterogeneous aspirations of individuals
into collective ways in which visions of sustainable society can be achieved.
References
Asad, M., Dantec, C. A. L., Nielsen, B., Diedrick, K. (2017). Creating a Sociotechnical API: Designing
City-Scale Community Engagement. In Proceedings of the 2017 CHI Conference on Human
Factors in Computing Systems (CHI '17). 2295–2306.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Bennett, W. L., Segerberg, A. (2012) The logic of connective action. Information, Communication &Society, 15(5), pages 739–768.
Bouvier, G., Machin, D. (2018) Critical Discourse Analysis and the challenges and opportunities of social
media, Review of Communication, 18(3), pages 178–192.
Bruns, A., Burgess, J. (2011). The use of Twitter hashtags in the formation of ad hoc publics. In
Proceedings of the 6th European consortium for political research (ECPR) general conference
2011. pages 1–9.
Brynskov, M., Heijnen, A., Balestrini, M., Raetzsch, C. (2018). Experimentation at scale: Challenges formaking urban informatics work. Smart and Sustainable Built Environment, 7(1), pages 150–163.
Cammaerts, B. (2012). Protest Logics and the Mediation Opportunity Structure. European Journal ofCommunication. 27(2), pages 117-134.
Chen, K., Aitamurto, T. (2019). Barriers for Crowd’s Impact in Crowdsourced Policymaking: Civic Data
Overload and Filter Hierarchy. International Public Management Journal, 22(1), pages 99-126.
Cuquet, M., Fensel, A. (2018). The societal impact of big data: A research roadmap for Europe.
Technology in Society, 54, pages 74–86.
Diani, M. (2015) The cement of civil society: studying networks in localities. Cambridge University Press,
Cambridge.
Foellmer, S., Lünenborg, M., Raetzsch, C. (2018). Media Practices, Social Movements, andPerformativity: Transdisciplinary Approaches. Routledge, Abingdon.
Foth, M., Brynskov, M. (2016). Participatory Action Research for Civic Engagement. In: Eric G., Paul M.
(Eds.), Civic Media: Technology, Design, Practice, pp. 563-580.
Foth, M., Choi, J. H., Satchell, C. (2011). Urban informatics. In Proceedings of the ACM 2011
Conference on Computer Supported Cooperative Work, pages 1–8.
Gordon, Eric; Mihailidis, Paul (eds.) (2016). Civic Media: Technology, Design, Practice (1 ed.).
Cambridge MA: The MIT Press.
Hamm, A., Shibuya, Y., Ullrich, S., Cerratto Pargman, T. (2021). What Makes Civic Tech Initiatives To
Last Over Time? Dissecting Two Global Cases. In Proceedings of Conference on Human Factors
in Computing Systems (CHI ‘21).

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Hamm, A., Lin, Z. (2019). Why Drones for Ordinary People? Digital Representations, Topic Clusters,
and Techno-Nationalization of Drones on Zhihu. Information, 10(8), pages 256.
https://doi.org/10.3390/info10080256
Karpf, D. (2017) Analytic Activism: Digital Listening and the New Political Strategy. Oxford University
Press, New YorkKim, J.-N., Grunig, J. E., Ni, L. (2010). Reconceptualizing the Communicative Action of Publics:
Acquisition, Selection, and Transmission of Information in Problematic Situations. International
Journal of Strategic Communication, 4(2), pages 126–154
Koch, F. Krellenberg, K. (2018). How to Contextualize SDG 11? Looking at Indicators for Sustainable
Urban Development in Germany. ISPRS International Journal of Geo-Information. 7 (12), pages
464.
Köhler, J., Geels, F. W., Kern, F., Markard, J., Onsongo, E., Wieczorek, A., Alkemade, F., Avelino, F.,
Bergek, A., Boons, F., Fünfschilling, L., Hess, D., Holtz, G., Hyysalo, S., Jenkins, K., Kivimaa, P.,
Martiskainen, M., McMeekin, A., Mühlemeier, M. S., Nykvist, B., Pel, B., Raven, R., Rohracher,
H., Sandén, B., Schot, J., Sovacool, B., Turnheim, B., Welch, D., Wells, P. (2019). An agenda forsustainability transitions research: State of the art and future directions. Environmental Innovationand Societal Transitions, 31, pages 1–32.
Liu, C., Balestrini, M., Vilaza, N. (2019). From Social to Civic: Public Engagement With IoT in Places
and Communities. In: Alessandro S., Margot, B., Paul R. (Eds.), Social Internet of Things,
Springer, Cham.
Mattoni, A. (2020). A Media-in-practices approach to investigate the nexus between digital media andactivists’ daily political engagement. International Journal of Communication, 14, pages 28282845.
Mattoni, A. (2016). A situated understanding of digital technologies in social movements. Media ecology
and media practice approaches. Social Movement Studies, 16(4), pages 494-505.
Maus, J. (2014). ODOT embarks on “big data” project with purchase of Strava dataset.
https://bikeportland.org/2014/05/01/odot-embarks-on-big-data-project-with-purchase-of-stravadataset-105375 (accessed 05.31.2021)
Milan, S. (2015). From Social Movements to Cloud Protesting: The Evolution of Collective Identity.
Information, Communication & Society, 18(8), pages 887-900.

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Papacharissi, Z. (2016). Affective publics and structures of storytelling: sentiment, events and mediality.
Information, Communication & Society, 19(3), pages 307–324.
Portland Bureau of Transportation, (2018). PBOT partners with Portland startup Ride Report for bicycle
data collection. https://content.govdelivery.com/accounts/ORPORTLAND/bulletins/1ea6499(accessed 05.31.2021)
Portland Bureau of Transportation (2013). First-in-U.S. bike counter installed on Hawthorne Bridge
thanks to Cycle Oregon. https://www.portlandoregon.gov/transportation/article/407186 (accessed
05.31.2021)
Sengers, F., Wieczorek, A.J., Raven, R. (2019). Experimenting for Sustainability Transitions: A
Systematic Literature Review. Technological Forecasting and Social Change, 145, pages 153-164.
Raetzsch, C., Pereira, G., Vestergaard, L.S, Brynskov, M. (2019). Weaving Seams With Data:
Conceptualizing City Apis as Elements of Infrastructures. Big Data & Society, 6(1).
Raetzsch, C., Brynskov, M. (2017). Desafiando as Fronteiras Do Jornalismo Por Meio de Objetos
Comunicativos: Berlim Como Uma Cidade Bike-Friendly E #radentscheid [Challenging theBoundaries of Journalism Through Communicative Objects: Berlin as a Bike-Friendly City and#radentscheid]. Parágrafo: Revista Científica de Comunicação Social da FIAM-FAAM, 5(2), pages
110-127.
San Francisco Bicycle Coalition (n.d.). San Francisco About. https://sfbike.org/about/ (accessed
05.31.2021)
San Francisco Municipal Transportation Agency (2013). SFMTA Board Approves Bicycle Barometer.
https://archives.sfmta.com/cms/apress/SFMTABoardApprovesBicycleBarometer.htm (accessed
05.31.2021)
Seattle Neighborhood Greenways (n.d.). Basic Bike Network What is “the Basic Bike Network”?
https://seattlegreenways.org/basicbikenetwork/ (accessed 05.31.2021)
Thorson, K., Medeiros, M., Cotter, K., Chen, Y., Rodgers, K., Bae, A., Baykaldi, S. (2020). Platform
Civics: Facebook in the Local Information Infrastructure. Digital Journalism, 8(10), pages 12311257.
United Nations (2018). Indicator 11.3.2: Proportion of cities with a direct participation structure of civilsociety in urban planning and management that operate regularly and democratically.
https://unstats.un.org/sdgs/metadata/?Text=&Goal=11&Target=11.3 (accessed 05.31.2021)

27nd International Sustainable Development Research Society Conference, Mid Sweden University, 13 – 15 July 2021

Vision Zero Network (n.d.). Vision zero network About https://visionzeronetwork.org/about/what-isvision-zero/ (accessed 05.31.2021)
Vlachokyriakos, V., Crivellaro, C., Le Dantec, C., Gordon, E., Wright, P., Olivier, P. (2016). Digital
Civics. Citizen Empowerment With and Through Technology. In Proceedings of the 2016 CHI
Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ‘16). 1096–
1099.
Von Wirth, T., Fuenfschilling, L., Frantzeskaki, N., Coenen, L. (2018). Impacts of Urban Living Labs on
Sustainability Transitions: Mechanisms and Strategies for Systemic Change ThroughExperimentation. European Planning Studies, 27(2), pages 229-257.
Wang, R., Liu, W. Gao, S. (2016). Hashtags and information virality in networked social movement:
Examining hashtag co-occurrence patterns, Online Information Review, 40(7), pages 850–866.
Werbeloff, L, Brown, R. Loorbach, D (2016). Pathways of System Transformation: Strategic Agency to
Support Regime Change. Environmental Science & Policy, 66, pages 119-128.
Wells, C. (2015). The Civic Organization and the Digital Citizen: Communicating Engagement in a
Networked Age. Oxford University Press, New York.
Willig, Carla (2014). “Discourses and discourse analysis.” In U. Flick (ed.) The SAGE handbook ofqualitative data analysis. Thousand Oaks: SAGE, pages 341-353.
Wonneberger, A., Hellsten, I.R., Jacobs, S.H.J. (2020). Hashtag activism and the configuration ofcounterpublics: Dutch animal welfare debates on Twitter, Information, Communication & Society,pages 1–18.
World Economic Forum (2013). The Future Role of Civil Society.
http://www3.weforum.org/docs/WEF_FutureRoleCivilSociety_Report_2013.pdf (accessed
05.31.2021)
Zins, C. (2007). Conceptual approaches for defining data, information, and knowledge. Journal of theAmerican Society for Information Science and Technology. 58(4), pages 479–493.