- From: Dimitrov, Dimitar <Dimitar.Dimitrov@gesis.org>
- Date: Mon, 16 Dec 2024 13:13:09 +0000
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- Beyond Facts - 5th International Workshop on Computational Methods for Online Discourse Analysis (BeyondFacts’25) https://beyondfacts2025.wordpress.com/ Collocated with TheWebConf (WWW) 2025 28 April - 2 May 2025, Sydney, Australia NEWS ==> Submission deadline extended to January 1, 2025 ==> Submissions now open at https://easychair.org/conferences/?conf=beyondfacts25 * Submission: December 20, 2024 → January 1, 2025 * Notification: January 20, 2025 → January 27, 2025 * Paper Camera-Ready: February 2, 2025 → February 7, 2025 * Proceedings published by ACM as Companion Proceedings of TheWebConf 2025 SUMMARY Expressing opinions and interacting with others on the Web has led to the production of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts (events, entities). This data constitutes a valuable source of insights for studies into misinformation spread, bias reinforcement, echo chambers or political agenda setting. Computational methods, mostly from the field of NLP, have emerged that tackle a wide range of tasks in this context, including argument and opinion mining, claim detection, checkworthiness detection, stance detection or fact verification. However, computational models require robust definitions of classes and concepts under investigation. Thus, these computational tasks require a strong interdisciplinary and epistemological foundation, specifically with respect to the underlying definitions of key concepts such as claims, arguments, stances, check-worthiness or veracity. This requires a highly interdisciplinary approach combining expertise from fields such as communication studies, computational linguistics and computer science. As opposed to facts, claims are inherently more complex. Their interpretation strongly depends on the context and a variety of intentional or unintended meanings, where terminology and conceptual understandings strongly diverge across communities. From a computational perspective, in order to address this complexity, the synergy of multiple approaches, coming both from symbolic (knowledge representation) and statistical AI seem to be promising to tackle such challenges. This workshop aims at strengthening the relations between these communities, providing a forum for shared works on the modeling, extraction and analysis of discourse on the Web. It will address the need for a shared understanding and structured knowledge about discourse data in order to enable machine-interpretation, discoverability and reuse, in support of scientific or journalistic studies into the analysis of societal debates on the Web. Beyond research into information and knowledge extraction, data consolidation and modeling for knowledge graphs building, the workshop targets communities focusing on the analysis of online discourse, relying on methods from machine learning, natural language processing, large language models and Web data mining. These include communities involving social sciences, information science as well as computer science concerned with: * discourse analysis * social web mining * argumentation mining * computational fact-checking * mis- and dis-information spread * bias and controversy detection and analysis * stance / viewpoint detection and representation * opinion mining * rumor, propaganda and hate-speech detection * computational journalism BeyondFacts provides a meeting point for these related but distinct communities that address similar or closely related questions from different perspectives and in different fields, using different models and definitions of the main notions of interest. Often these communities apply their research in particular domains, such as scientific publishing, medicine, journalism or social science. Therefore, the workshop is particularly interested in works that apply an interdisciplinary approach, such as works on computational social sciences or computational journalism. TOPICS OF INTEREST * Large language models for online discourse * Computational fact-checking / truth discovery * Computational journalism * Social, ethical and legal aspects of online discourse * Bias and controversy detection and analysis * Stance and viewpoint discovery * Interpretability / explainability of computational methods for discourse analysis * Rumour, propaganda and hate-speech detection * Intent discovery for claims * Integration, aggregation, linking and enrichment of discourse data * Multilingual analysis of online discourse data * Ontologies and data models for online discourse data * Reuse and extension of existing models such as schema.org and Wikidata * KGs and knowledge extraction techniques in the context of online discourse * Semantic and exploratory search of online discourse data * Argumentation and reasoning over online discourse * Recommender systems for discourse data * Quality, uncertainty, provenance, and trust of discourse data * Dealing with online audiovisual content * Benchmarks and training data for extraction, verification or linking of discourse data * Use-cases, applications and cross-community interfaces SUBMISSION We welcome the following types of contributions: * Full papers (up to 10 pages; max 8 pages for the main content + max 2 pages for both references and appendices) may contain original research of relevance to the workshop topics. * Short papers (up to 6 pages; max 4 pages for the main content + max 2 pages for both references and appendices) may contain original research in progress of relevance to the workshop topics. * System/Demo papers (up to 6 pages; max 4 pages for the main content + max 2 pages for both references and appendices) may contain descriptions of prototypes, demos or software systems related to the workshop topics. * Resource papers (up to 6 pages; max 4 pages for the main content + max 2 pages for both references and appendices) may contain descriptions of resources related to the workshop topics, such as datasets, ontologies, knowledge graphs, ground truth datasets, etc. * Position/Vision papers (up to 6 pages; max 4 pages for the main content + max 2 pages for both references and appendices) may discuss vision statements or arguable opinions related to the workshop topics. Workshop papers must be self-contained and in English. They should not have been previously published, should not be considered for publication, and should not be under review for another workshop, conference, or journal. The review process will be single-blind. All submissions must adhere to the ACM template (https://www.acm.org/publications/proceedings-template), using the traditional double-column format. Word users may use *Word Interim* Template, and latex users may use *sample-sigconf* template. Overleaf users may want to use the ACM proceedings template available in Overleaf (https://www.overleaf.com/latex/templates/association-for-computing-machinery-acm-sig-proceedings-template/bmvfhcdnxfty). Please submit your contributions electronically in PDF format via the EasyChair conference submission system at: https://easychair.org/conferences/?conf=beyondfacts25 For any enquiries, please send an email to the workshop organizers: https://beyondfacts2025.wordpress.com/ Papers will be evaluated according to their significance, originality, technical content, style, clarity, and relevance to the workshop. At least one author of each accepted contribution must register for the workshop and present the paper. Pre-prints of all contributions will be made available during the conference. IMPORTANT DATES * Submission: December 20, 2024 → January 1, 2025 * Notification: January 20, 2025 → January 27, 2025 * Paper Camera-Ready: February 2, 2025 → February 7, 2025 * Workshop at WWW2025: April 28 - 29, 2025. All submission deadlines are end-of-day in the Anywhere on Earth (AoE) time zone. KEYNOTES * TBA AWARD * All contributions are eligible for the "Best Paper" award. PREVIOUS EDITIONS * BeyondFacts 2021: https://knod2021.wordpress.com/ * BeyondFacts 2022: https://knod22.wordpress.com/ * BeyondFacts 2023: https://beyondfacts2023.wordpress.com/ * BeyondFacts 2024: https://beyondfacts2024.wordpress.com/ ORGANIZING COMMITTEE * Konstantin Todorov (University of Montpellier, CNRS, LIRMM, France) * Stefan Dietze (Heinrich-Heine-University Düsseldorf & GESIS, Germany) * Pavlos Fafalios (Technical University of Crete and ICS-FORTH, Greece) * Dimitar Dimitrov (GESIS, Germany) PROGRAM COMMITTEE * Katarina Boland, Heinrich Heine University, Germany * Alexander Brand, University of Hildesheim, Germany * Sandra Bringay, Paul Valéry University of Montpellier, France * Elena Cabrio, University Cote D'Azur, France * John Culbert, GESIS, Germany * Ronald Denaux, Amazon.com, Spain * Gianluca Demartini, University of Queensland, Australia * Vasilis Efthymiou, Harokopio University of Athens and FORTH-ICS, Greece * Michael Färber, TU Dresden, Germany * Agata Gurzawska, Trilateral, Ireland * Salim Hafid, LIRMM, Université Montpellier, France * Kyle Hamilton, Technological University Dublin, Ireland * Daniel Hardt, Copenhagen Business School, Denmark * Andreea Iana, University of Mannheim, Germany * Mali Jin, University of Sheffield * Mathieu Lafourcade, University of Montpellier, France * Stephan Linzbach, GESIS, Germany * Julio Amador Diaz Lopez, Imperial College London, UK * Philipp Meier, GESIS, Germany * Ioana Manolescu, INRIA, France * Yannis Marketakis, University of Crete and FORTH-ICS, Greece * Diana G Maynard, Sheffield, UK * Petr Motlicek, Idiap, Switzerland * Michalis Mountantonakis, University of Crete and FORTH-ICS, Greece * Preslav Nakov, MBZUAI, United Arab Emirates * Wolfgang Otto, GESIS, Germany * Panagiotis Papadakos, FORTH-ICS, Greece * Katerina Papantoniou, FORTH-ICS, Greece * José Manuel Gómez Pérez, Expert.AI, Spain * Ensiyeh Raouffi, LIRMM, Université Montpellier, France * Achim Rettinger, University of Trier, Germany * Mathieu Roche, CIRAD, France * François Scharffe, LIRMM, Université Montpellier, France * Sebastian Schellhammer, GESIS, Germany * Daniel Schwabe, Pontificia Universidade Católica, Brazil * Kostas Stefanidis, Tampere University, Finland * Pedro Szekely, University of South California, USA * Andon Tchechmedjiev, Ecoles des Mines d’Alès, France * Yannis Tzitzikas, University of Crete and FORTH-ICS, Greece * Ran Yu, University of Bonn, Germany Dr. Dimitar Dimitrov Head of team Information Extraction & Linking KTS / Information Extraction & Linking [cid:b560be3c-c013-4435-99eb-6893bc911aef]<https://www.gesis.org/en/home> Unter Sachsenhausen 6-8 | 50667 Köln +49 (0) 221 47694 512 dimitar.dimitrov@gesis.org<mailto:dimitar.dimitrov@gesis.org> [Ein Bild, das Symbol, Logo, Schrift, Grafiken enthält. 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Received on Monday, 16 December 2024 13:13:18 UTC