The workshop on Computational methods for emerging problems in disinformation analysis (DisA) is organized during the International Conference on Computational Science (ICCS) , from June 3rd-5th 2020 in Amsterdam.
DisA aims to bring together researchers and scientists of computational science who are pioneering disinformation analysis methods to discuss problems and solutions in this area, to identify new issues, and to shape future directions for research. Furthermore, prospective researchers are invited to send papers concerning disinformation detection methods and architectures, explainability of information processing methods and decision support systems as well as their security.
Workshop’s 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
You can see more information here.