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Call: KnOD 2022 @ TheWebConf

Thursday, February 10, 2022

Event Details

- Beyond Facts -
2nd International Workshop on Knowledge Graphs for Online Discourse Analysis (KnOD)

Online Event, collocated with TheWebConf (WWW) 2022
25-29 April 2022, hosted by Lyon, France


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. While knowledge graphs promise to provide the key to a Web of structured information, they are mainly focused on facts without keeping track of the diversity, connection or temporal evolution of online discourse data. 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 computational social science, to argumentation mining, fact-checking, or viewpoint/stance detection.

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 KG building, the workshop targets communities focusing on the analysis of online discourse, relying on methods from machine learning, natural language processing and Web data mining. These include communities on:

* 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
* rumour, propaganda and hate-speech detection
* computational journalism

KnOD 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.


* Ontologies and data models for online discourse data
* Reuse and extension of existing models such as and Wikidata
* Knowledge graphs and knowledge extraction techniques in the context of 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
* Rumour, propaganda and hate-speech detection
* Intent discovery for claims
* Interpretability and explainability of online discourse analyses
* Integration, aggregation, linking and enrichment of discourse data
* 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


* Full papers (up to 12 pages; max 8 pages for the main content + max 2 pages for appendixes + max 2 pages for references) may contain original research of relevance to the workshop topics.
* Short papers (up to 8 pages; max 4 pages for the main content + max 2 pages for appendixes + max 2 pages for references) may contain original research in progress of relevance to the workshop topics.
* Demo and system papers (up to 8 pages; max 4 pages for the main content + max 2 pages for appendixes + max 2 pages for references) may contain descriptions of prototypes, demos or software systems related to the workshop topics.
* Resource papers (up to 8 pages; max 4 pages for the main content + max 2 pages for appendixes + max 2 pages for references) may contain descriptions of resources related to the workshop topics, such as ontologies, knowledge graphs, ground truth datasets, etc.
* Position papers (up to 8 pages; max 4 pages for the main content + max 2 pages for appendixes + max 2 pages for references) may discuss vision statements or arguable opinions related to the workshop topics.
* Posters (up to 2 pages) may contain preliminary work in progress 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. All submissions must adhere to the ACM template ( ), using the traditional double-column format. Word users may use Word Interim Template, and latex users may use sample-sigconf template.

Papers have to be submitted electronically via the EasyChair conference submission system:


* Papers due: February 3, 2022
* Paper notifications: March 3, 2022
* Paper camera-ready versions due: March 10, 2022
* Workshop: April 25/26, 2022


* All contributions are eligible for the "Best Paper" award


* KnoD 2021:


* Konstantin Todorov (University of Montpellier & LIRMM, France)
* Stefan Dietze (Heinrich-Heine-University Düsseldorf & GESIS, Germany)
* Pavlos Fafalios  (ICS-FORTH, Greece)


* Katarina Boland, GESIS, Germany
* Alexander Brand, University of Hildesheim, Germany
* Sandra Bringay, Paul Valéry University of Montpellier, France
* Giovanni Luca Ciampaglia, University of South Florida, USA
* Ronald Denaux, Expert.AI, Spain
* Gianluca Demartini, University of Queensland, Australia
* Vasilis Efthymiou, FORTH, Greece
* Michael Färber, Karlsruhe Institute of Technology, Germany
* Mario Haim, University of Leipzig, Germany
* Kyle Hamilton, Technological University Dublin, Ireland
* Daniel Hardt, Copenhagen Business School, Denmark
* Julio Amador Diaz Lopez, Imperial College London, UK
* Pranava Madhyastha, City University of London, UK
* Ioana Manolescu, INRIA, France
* Petr Motlicek, Idiap Research Institute, Switzerland
* Preslav Nakov, Qatar Computing Research Institute, Qatar
* Panagiotis Papadakos, FORTH, Greece
* José Manuel Gómez Pérez, Expert.AI, Spain
* Achim Rettinger, University of Trier, Germany
* Kostas Stefanidis, Tampere University, Finland
* Daniel Schwabe, Pontificia Universidade Católica, Brazil
* Pedro Szekely, University of South California, USA
* Andon Tchechmedjiev, Ecoles des Mines d’Alès, France
* Yannis Tzitzikas, FORTH, Greece
* Xiaofei Zhu, Chongqing University of Technology, China