- Submission deadline extended to February 21, 2021.
- We are excited to announce that Preslav Nakov and Daniel Schwabe will be our two keynote speakers! More information at https://knod2021.wordpress.com/keynotes/
Expressing opinions and interacting with others on the Web has led to the availability of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts (related events or entities). Discourse data constitutes a valuable source of insights for studies into misinformation spread, bias reinforcement, echo chambers or political agenda setting and is crucial as training/testing data for various NLP tasks. While knowledge graphs (KGs) 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 providing a forum for shared works on the modeling, extraction and analysis of discourse on the Web, strengthening the relations between the fields of natural language processing (NLP,, computational linguistics, semantic web, knowledge graphs, argument mining and modeling, social sciences/communication studies, web science and computational social sciences. 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.
Topics of interest
* Knowledge graphs and knowledge extraction techniques in the context of online discourse
* Computational fact-checking / truth discovery
* 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 analysis methods
* Ontologies and data models for online discourse data
* Reuse and extension of existing models such as schema.org
* 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
* Benchmarks and training data for extraction, verification or linking of discourse data
* Use-cases, applications and cross-community interfaces
* Preslav Nakov (Qatar Computing Research Institute, Qatar): Detecting the "Fake News" Before It Was Even Written, Media Literacy, and Flattening the Curve of the COVID-19 Infodemic
* Daniel Schwabe (PUC-Rio, Brasil): Trust and Mis/Disinformation - a Dispute of Narratives
* Full papers (up to 8 pages, plus references and appendix) may contain original research of relevance to the workshop topics.
* Short papers (up to 4 pages, plus references and appendix) may contain original research in progress of relevance to the workshop topics.
* Demo and system papers (up to 4 pages, plus references and appendix) may contain descriptions of prototypes, demos or software systems related to the workshop topics.
* Resource papers (up to 4 pages, plus references and appendix) may contain descriptions of resources related to the workshop topics, such as ontologies, knowledge graphs, ground truth datasets, etc.
* Position papers (up to 4 pages, plus references and appendix) 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.
All submissions must be written in English and adhere to the ACM template and format (https://knod2021.wordpress.com/dates-and-submission/
Papers have to be submitted electronically via the EasyChair conference submission system: https://easychair.org/conferences/?conf=knod2021
* Papers due: February 21, 2021
* Paper notifications: March 7, 2021
* Paper camera-ready versions due: March 14, 2021
* Workshop: April 19/20, 2021
* All contributions are eligible for the “Best KnOD Paper” award
* Konstantin Todorov (University of Montpellier & LIRMM, France)
* Stefan Dietze (Heinrich-Heine-University Düsseldorf & GESIS, Germany)
* Pavlos Fafalios (ICS-FORTH, Greece)
* Harith Alani, KMI, The Open University, UK
* Katarina Boland, GESIS, Germany
* Sandra Bringay, Paul Valéry University of Montpellier, France
* Gianluca Demartini, University of Queensland, Australia
* Ronald Denaux, Expert.AI, Spain
* Vasilis Efthymiou, FORTH, Greece
* Michael Färber, Karlsruhe Institute of Technology, Germany
* Jose Manuel Gomez-Perez, Expert.AI, Spain
* Daniel Hardt, Copenhagen Business School, Denmark
* Ioana Manolescu, INRIA Saclay and LIX/Ecole Polytechnique, France
* Preslav Nakov, Qatar Computing Research Institute, Qatar
* Panagiotis Papadakos, FORTH, Greece
* Rajesh Piryani, South Asian University, New Delhi, India
* Daniel Schwabe, Pontifícia Universidade Católica do Rio de Janeiro, Brazil
* Kostas Stefanidis, Tampere University, Finland
* Pedro Szekely, University of Southern California, USA
* Andon Tchechmedjiev, Ecoles des Mines d’Alès, France
* Yannis Tzitzikas, FORTH, Greece
* Xiaofei Zhu, Chongqing University of Technology, China