WORKSHOP REPORT

Report on the Second International Workshop
on Narrative Extraction from Texts(Text2Story 2019)
Alı́pio M. Jorge1,2 , Ricardo Campos1,3 , Adam Jatowt4 , Sumit Bhatia5 , Arian
Pasquali1 , João Paulo Cordeiro1,6 , Conceição Rocha1 , and Vı́tor Mangaravite7
1

INESC TEC, Portugal
University of Porto, Portugal
3Ci2 - Smart Cities Research Center, Polytechnic Institute of Tomar, Portugal
4
Kyoto University, Japan
5IBM Research AI, India
6
University of Beira Interior, Portugal
7
UFMG - Universidade Federal de Minas Gerais, Brazil
2Abstract
The Second International Workshop on Narrative Extraction from Texts (Text2Story’19[http://text2story19.inesctec.pt/]) was held on the 14th of April 2019, in conjunction with the 41st European Conference on Information Retrieval (ECIR 2019) in Cologne,Germany. The workshop provided a platform for researchers in IR, NLP, and design andvisualization to come together and share the recent advances in extraction and formal representation of narratives. The workshop consisted of two invited talks, ten research paper
presentations, and a poster and demo session. The proceedings of the workshop are available
online at http://ceur-ws.org/Vol-2342/

1

Introduction

The continuous growth of social networks such as Facebook and Twitter, together with anever-increasing presence of traditional news media outlets on the Web, has changed the way
information is being generated and consumed. Rather than relying on a few sources of information about an event or a news item topic (e.g., US and China trade war ), readers
now have easy access to the content via multiple, sources (news websites, Facebook posts,Web Archives, etc.) produced by disparate content creators such as journalists, subject
matter experts, and social media users. Further, active reader participation also occurs in
the comments section of news articles with discussions lasting over days, weeks or possibly,months. Such a stream of continuously evolving information makes it unmanageable andACM SIGIR Forum

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time-consuming for an interested reader to track, read, and process different sources of information to keep up with all the developments and various aspects of the topic of interest.
Automated narrative extraction from text offers a compelling approach to this problem andinvolves identifying the sub-set of interconnected raw documents, extracting the critical narrative/story elements, and representing them in a more adequate final form (e.g., time-lines)that conveys the key points of the story in an easy to understand format to the readers or in
an intermediate structured formalism that can feed further steps. Although information extraction and natural language processing have made significant progress towards automaticinterpretation of texts, the problem of fully identifying and relating the different elements ofa narrative present in a document (set) still presents significant unsolved challenges [John etal., 2016].
The workshop brought together a diverse set of participants from academia and industry(about ≈ 40 participants) with expertise in fields such as information retrieval, naturallanguage processing, and design and visualization. The workshop program consisted of two
invited keynote talks, ten research papers, and a poster and demos session. The papers
presented at the workshop covered diverse aspects of the narrative extraction problem ranging
from formal models [Zahid et al., 2019; Staykovski et al., 2019; Metilli et al., 2019; Raiyani etal., 2019; Croce et al., 2019], narrative presentation and visualization [Vani and Antonucci,2019; Rehm et al., 2019] to different applications such as healthcare [Dirkson et al., 2019],
novels [Motwani et al., 2019], and identifying radicalizing narratives [Denaux and GómezPérez, 2019].
The Program Chairs were Alı́pio Jorge, Ricardo Campos, Adam Jatowt and Sumit Bahtia.
The proceedings were setup by our Proceedings Chairs João Paulo Cordeiro and ConceiçãoRocha. Arian Pasquali was Web Chair and Vitor Mangaravite was in charge of dissemination.
We also had Arian Pasquali and Andreas Spitz as Session Chairs.

2Keynotes

2.1

Iryna Gurevych on Automated Claim Validation

Professor Iryna Gurevych from Technische Universität Darmstadt talked about the crucial
task of automatic validation of claims. Claim validations is a difficult task that often requires
expert human judgment and Iryna presented an overview of the state-of-the-art on automatedclaim validation and how these methods compare with manual validation. She also presented
an overview of different datasets and benchmarks that can be used for evaluating automatedclaim validation approaches.

2.2

Miguel Martinez on Automatic Media Analysis

Miguel Martinez, the co-founder and Chief Data Scientist of Signal AI1 , provided a uniqueindustry perspective by describing the real-time online media analysis being carried out at
Signal AI. He discussed the challenges in online monitoring and real-time analysis of media
sources for various client companies. Companies are interested in the emerging narrativearound their products, and media campaigns and large scale monitoring and analysis ofnews and social media can provide valuable insights to them. The talk touched on various
1

https://www.signal-ai.com/

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challenges in developing such solutions and how the IR community can contribute to address
those challenges.

3Research Papers

The papers presented at the workshop covered different facets of narrative extraction fromtext, which we briefly summarize here.
Narrative Detection and Extraction: Zahid et al. [2019] described an approach toautomatically segment news story text according to news schema categories such as action,reaction, and history. Key sentences from each segment can then be sieved together to construct the underlying narrative. Staykovski et al. [2019] presented a comparative evaluationof sparse (such as tf-idf) and dense (embeddings based) representations for clustering news
articles into topical clusters. Metilli et al. [2019] presented their software system for event
detection and classification, as part of a larger software framework developed for narrative
detection and extraction in digital libraries. Raiyani et al. [2019] presented a system for
automatic event extraction from Portuguese texts. The proposed approach is based on apipeline of specialized natural language processing tools; namely, a part-of-speech tagger,a named entity recognizer, a dependency parser, semantic role labeling, and a knowledge
extraction module. Croce et al. [2019] proposed a machine learning framework combining
Hidden Markov Models and SVM to segment drama texts into core dramatic units such asactions, agents and conflicts.
Narrative Presentation and Visualization: Vani and Antonucci [2019] described aframework for presenting visual summaries of narrative texts. Different characters, events,
and their interconnections are represented as a graph and provide a succinct summary of
the narrative to the end-user. Rehm et al. [2019] described their vision of a semantic storytelling system that can identify different characters, events, and plotlines from an input
document corpus as a means to present the extracted storylines to the end-users (journalists,researchers, etc.) and aid their respective knowledge processing workflows.
Applications: Motwani et al. [2019] presented an interesting application of narrative extraction applied to detective novels where they create evidence summaries for different charactersin the novel that can help determine the culprits. Dirkson et al. [2019] presented their studyof online patient communities that provided insights about the different psycho-linguistic features that can aid in identification of narrative posts in such online discussions. Specifically,
they reported that social media posts describing patient narratives are generally written inpast tense, and contain health-related words and first-person pronouns. On the other hand,posts containing non-narrative text are often written in future tense, and use emotional support words and second-person pronouns. Denaux and Gómez-Pérez [2019] presented theirapproach for detecting radicalizing text so that its spread can be minimized. They argued
for the need of building such systems by utilizing the research done in social sciences to understand key characteristics of radicalization narratives and presented taxonomies to capture
these characteristics. They also described a rule based system that uses these taxonomies toannotate presence of radical narrative text in online documents.

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4Poster and Demo Session

All the accepted research papers were also given an opportunity to showcase their work during
the poster session to allow for an informal setting for the workshop participants to discuss
the work and enable networking and socializing. In addition, the six following systems weredemonstrated during the demo sessions.
1. TopExNet: Topic Exploration in Entity-centric Networks of News Streams
by Andreas Spitz, Satya Almasian, Michael Gertz from Heidelberg University
http://topexnet.ifi.uni-heidelberg.de
2. TanBih: News Bias and Media Outlets Profiles
by Preslav Nakov from Qatar Computing Research Institutehttp://www.tanbih.org
3. ArgumentSearch : Argumentation Mining Search Engine
by Iryna Gurevych from Technische Universität Darmstadt
http://argumentsearch.com
4. Agatha: Platform for Criminal Police Investigation
by Kashyap Raiyani, Teresa Gonçalves, Paulo Quaresma, Vı́tor Beires Nogueira fromUniversity of Évora
http://www.agatha-osi.com/
5. YAKE Keyword Extraction: A Text Feature Based Automatic Keyword Extraction
Method for Single Documents
by Ricardo Campos, Vı́tor Mangaravite, Arian Pasquali, Alı́pio Jorge, Célia Nunes,Adam Jatowt from LIAAD INESC TEC / Ci2-IPT / FCUP / UBI / University ofKyoto
http://yake.inesctec.pt
6. Tell me stories: Interactive System for Automatically Generating Temporal Narratives
by Arian Pasquali, Vı́tor Mangaravite, Ricardo Campos, Alı́pio Jorge, Adam Jatowt
from LIAAD INESC TEC / Ci2-IPT / FCUP/ University of Kyoto
http://archive.tellmestories.pt, ECIR demo: http://demo.tellmestories.pt

5Future Directions

This was the second edition of the Text2Story workshop series. Our objective was to bring
together the interested participants from different geographies and research expertise tocollectively set the agenda for the emerging multi-disciplinary area of narrative extraction
from texts. In addition to the two workshops [Jorge et al., 2018, 2019a], we have also editeda Special Issue on Narrative Extraction from Texts (Text2Story) in Information Processing& Management (IPM) Journal2 that provides a good overview of mature research efforts inthe field [Jorge et al., 2019b]. We have received very positive response from the researchcommunity and the growing participation in the workshops underlines the relevance of thetopic. Thus, it is our aim to continue organizing the workshop series in IR and NLP venues
to develop the field further.
2

https://www.sciencedirect.com/science/article/abs/pii/S0306457319304455

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6

Programme Committee

The following researchers and industry experts have served on the Programme Committeeof the Text2Story’19 workshop:• Álvaro Figueira (University of Porto)• Arian Pasquali (University of Porto)• Bruno Martins (IST and INESC-ID - Instituto Superior Técnico, University of Lisbon)• Conceição Rocha (INESC TEC)
• Daniel Loureiro (University of Porto)• Daniel Gomes (FCT/Arquivo.pt)• Dhruv Gupta (Max Planck Institute for Informatics)• Federico Nanni (University of Mannheim)• Florian Boudin (Université de Nantes)• Gaël Dias (Normandie University)• Gerasimos Lampouras (The University of Sheffield)• Henrique Lopes Cardoso (University of Porto)• Jacobo Rouces (University of Gothenburg)• João Magalhães (New University of Lisbon)• João Paulo Cordeiro (Universidade da Beira Interior)• Pablo Gamallo (University of Santiago de Compostela)• Paulo Quaresma (Universidade de Evora)• Mark Finlayson (Florida International University)• Marc Spaniol (Université de Caen Normandie)• Mengdie Zhuang (The University of Sheffield)• Miguel Martinez-Alvarez (Signal)• Nicola Ferro (University of Padova)• Nina Tahmasebi (University of Gothenburg)• Nuno Moniz (LIAAD/INESC TEC)
• Udo Kruschwitz (University of Essex)• Sérgio Nunes (University of Porto)• Yihong Zhang (Kyoto University)• Vitor Mangaravite (LIAAD INESC TEC; UFMG)
Acknowledgements
We would like to thank ECIR2019 organizers for helping us to organize the workshop, ourkeynote speakers, the program committee, the paper authors, and the participants. Thiswork is partially funded by the ERDF through the COMPETE 2020 Programme withinproject POCI-01-0145-FEDER-006961, and by National Funds through the FCT as part ofproject UID/EEA/50014/2013.

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