Abstract
The problem of the fake news publication is not new and it already has been reported in ancient ages, but it has started having a huge impact especially on social media users. Such false information should be detected as soon as possible to avoid its negative influence on the readers and in some cases on their decisions, e.g., during the election. Therefore, the methods which can effectively detect fake news are the focus of intense research.
The main aim of this section is to bring together researchers and scientists from basic computing disciplines (computer science and mathematics), experts in legal and societal aspects as well as researchers from various application areas who are pioneering fake news analysis methods to discuss problems and solutions in this area, to identify new issues, and to shape future directions for research.
Topics
The list of possible topics includes, but is not limited to:
- The list of possible topics includes, but is not limited to:
- Detection fake news detection in social media
- Detection fake news detection in images and video
- Architectural frameworks and design for fake news detection
- Learning how to detect the fake news in the presence of concept drift
- Learning how to detect the fake news with limited ground truth access and on the basis of limited data sets, including one-shot learning
- Feature selection and extraction methods for fake news detection
- Proposing how to compare and benchmark the fake news detectors
- Case studies and real-world applications
- Legal and societal aspects of fake news detection
- Data protection and GDPR in fake news detection challenge
Session Chairs
- Prof. Michal Choras, UTP University of Science and Technology (Poland).
- Prof. Rafal Kozik, UTP University of Science and Technology ( Poland).
- Dr. Pawel Ksieniewicz, Wroclaw University of Science and Technology (Poland).
- Prof. Michal Wozniak, Wroclaw University of Science and Technology (Poland).
Program Committee
Evgenia F. Adamopoulou, ICCS, NTUA, Athens (Greece)
Tomasz Andrysiak, UTP University of Science and Technology (Poland)
Łukasz Apiecionek, Kazimierz Wielki University, Bydgoszcz (Poland)
Stan Assier, QWANT (France)
Robert Burduk, Wroclaw University of Science and Technology (Poland)
Sonia Collada, Expert System (France)
Konstantinos Demestichas (SocialTruth project coordinator), ICCS, NTUA, Athens (Greece)
Agata Gielczyk, Evgenia F. Adamopoulou, ICCS, NTUA, Athens (Greece)
Manik Gupta, LSBU, London (UK)
Dagmara Jaroszewska-Choras, Kazimierz Wielki University, Bydgoszcz (Poland)
George Koutalieris, ICCS, NTUA, Athens (Greece)
Iulia Lazar, Infocons (Romania)
Wojciech Mazurczyk, Warsaw University of Technology (Poland)
Giulia Venturi, Z&P (Italy)
Contact
Prof. Michal Wozniak
Department of Systems and Computer Networks, Faculty of Electronics
Wroclaw University of Science and Technology
Wybrzeze Wyspianskiego 27,50-370 Wroclaw, Poland
e-mail Michal.Wozniak@pwr.edu.pl
web: http://kssk.pwr.edu.pl/people/mwozniak
Additional Information
The session will be technically endorsement by IEEE SMC TC on Big Data Computing http://www.ieeesmc.org/technical-activities/cybernetics/big-data-computing as well by SocialTruth project (http://Socialtruth.eu), which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 825477.