The workshop on Computational methods for emerging problems in disinformation analysis is organized during the International Conference on Computational Science ICCS 2020 in Amsterdam, The Netherlands.
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 (Socialtruth.eu), which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 825477.
Information analysis is nowadays crucial for societies, single citizens in their everyday life (e.g. while travelling, shopping, browsing, communication etc.) as well for businesses and overall economy. The right to be informed is one of fundamental requirements allowing for taking right decisions in a small and large scale (e.g. elections).
However information spreading can be also used for disinformation. 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 or people watching media news (Internet, newspapers, tv etc.). 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.
Another problem and emerging challenge is coming from using automated information analysis and decision support systems (based on Artificial Intelligence (AI) and Machine Learning (ML) advances) as black-box single truth providers. If those information analysis systems are misused, attacked or fooled, their results will also lead to (dis-) information.
The main aim of this workshop is to bring together researchers and scientists computational science who are pioneering (dis-)information analysis methods to discuss problems and solutions in this area, to identify new issues, and to shape future directions for research. Moreover, we invite prospective researchers to send papers concerning (dis-)information detection methods and architectures, explainability of information processing methods and decision support systems as well as their security.
Topics of interest
- computational methods for (dis-) information analysis, especially in heterogenous types of data (images, text, tweets etc.)
- detection of fake news detection in social media
- images and video manipulation recognition
- architectural frameworks and design for (dis-)information detection
- aspects of explainability of information analysis systems and methods (including explainability of ML)
- adversarial attacks on information analysis
- explainability of deep learning
- 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
- proposing how to compare and benchmark the fake news detectors
- case studies and real-world applications
- human rights, legal and societal aspects of (dis-)information detection, including data protection and GDPR in practice
|Paper submission||13 December 2019|
|Notification of acceptance of papers||24 January 2020|
|Camera-ready papers||28 February 2020|
|Author registration||24 January – 28 February 2020|
|Conference||3-5 June 2020|
- Prof. Michal Choras, UTP University of Science and Technology, Poland e-mail: firstname.lastname@example.org
- Dr. Konstantinos Demestichas e-mail: email@example.com
Program committee (tenatative)
- Evgenia F. Adamopoulou, ICCS, NTUA
- Tomasz Andrysiak, UTP University of Science and Technology, Poland
- Łukasz Apiecionek, Kazimierz Wielki University, Bydgoszcz
- 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
- Agata Gielczyk, Evgenia F. Adamopoulou, ICCS
- Manuel Grana, University of the Basque Country, Spain
- Manik Gupta, LSBU, London
- Álvaro Herrero, University of Burgos, Spain
- Dagmara Jaroszewska-Choras, Kazimierz Wielki University, Bydgoszcz
- George Koutalieris, ICCS, NTUA
- Rafal Kozik, UTP University of Science and Technology, Poland
- Pawel Ksieniewicz, Wroclaw University of Science and Technology, Poland
- Iulia Lazar, Infocons, Romania
- Wojciech Mazurczyk, Warsaw University of Technology, Poland
- Giulia Venturi, Z&P, Italy
- Michal Wozniak, Wroclaw University of Science and Technology, Poland