DisA 2026 : Emerging Problems in Disinformation Analysis

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The workshop on Emerging Problems in Disinformation Analysis DisA 2026 is organized in conjunction with the IEEE International Conference on Big Data (IEEE Big Data 2026) in Phoenix, USA, in December 2026.

The workshop is held in a full virtual (online) format.

Key dates

Paper submission deadline: 20. October 2026
Notification to authors: 11. November 2026
Camera-ready papers: 20. November 2026
Workshop sessions — Phoenix, USA (virtual): 14-17 December 2026


About

Trustworthy information analysis is crucial for societies, single citizens in their everyday life (e.g., while traveling, shopping, browsing, communicating, etc.) as well as for businesses and the overall economy. The right to be informed is one of the fundamental requirements for making the right decisions on a small and large scale (e.g., elections). However, information spreading can also be used for disinformation. The problem of fake news publication is not new, and it has already 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 immediately to avoid its negative influence on the readers and their decisions. Still it is not easy to detect disinformation within the Big Data information digital world.

The main aim of this workshop is to bring together researchers and scientists who are pioneering (dis-)information analysis methods to discuss problems and solutions in this area, identify new issues, and shape future research directions. Disinformation (fake news) is one of the greatest and still unsolved challenges for societies and security. Moreover, the aspects of cyber security, trustworthy AI and big data analysis will be discussed.

Topics of interest

We particularly invite works focusing on the following:
- methods for (dis-)information analysis, especially in heterogeneous data types (images, text, tweets etc.)
- detection of fake news detection in social media
- images and video manipulation recognition
- audio manipulation detection
- deepfakes detection and understanding in audio and images
- 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
- LLMs for fake news/disinformation detection
- proposing how to compare and benchmark the fake news detectors
- case studies and real-world applications for end-users
- human rights, legal and societal aspects of (dis-)information detection, including data protection and GDPR in practice
- impact of disinformation/fake news on societies and the economy
- demonstrations and papers presenting particular tools to fight disinformation

Submission instructions and proceedings

All papers should be submitted electronically via the IEEE Big Data 2026 submission system. All submissions will be blind reviewed by the Program Committee on the basis of technical quality, relevance to the workshop's topics of interest, originality, significance, and clarity.

Author names and affiliations must not appear in the submissions, and bibliographic references must be adjusted to preserve author anonymity. Submissions failing to comply with paper formatting and author anonymity requirements will be rejected without review. Because of the double-blind review process, non-anonymous papers that have been issued as technical reports or similar cannot be considered for DISA 2026.

Workshop chairs

Organized by researchers from Bydgoszcz University of Science and Technology, Warsaw University of Technology, and Universitat Oberta de Catalunya.

Michał Choraś
Bydgoszcz University of Science and Technology, Poland
[email protected]

Rafał Kozik
Bydgoszcz University of Science and Technology, Poland
[email protected]

Wojciech Mazurczyk
Warsaw University of Technology & IDEAS Research Centre, Warsaw, Poland
[email protected]

David Megias
Universitat Oberta de Catalunya, Barcelona, Spain
[email protected]