The selection of the most important and recent publications related to the project REBELION:
- Machová, Kristína – Mikula, Martin – Szabóová, Martina – Mach, Marián. Sentiment and Authority Analysis in Conversational Content. In Computing and Informatics, Vol. 37, No. 3(2018), s. 737-758, ISSN 1335-9150, DOI: 10.4149/cai_2018_3_737. IF 0.410, WOS 2017 = Q4, CC.
- KAŠŠÁK, Ondrej – KOMPAN, Michal – BIELIKOVÁ, Mária. Acquisition and Modelling of Short-Term User Behaviour on the Web: A Survey. In Journal of Web Engineering. Vol. 17, iss. 5 (2018), s. 23-70. ISSN 1540-9589, DOI: 10.13052/jwe1540-9589.1752. IF 2017 = 0.311, WOS 2017 = Q4, SJR 2017 = Q4.
- Machová, Kristína, Ledecký, Miroslav. Search for Exceeding Web Reviewers – Authorities and Trolls Using Genetic Programming. In: 1st International Conference on Advances in Signal Processing and Artificial Intelligence, Aspai’ 2019: 20. – 22.3.2019, Barcelona, IFSA Publishing, S. L., 2019, 119-122, ISBN 978-84-09-10127-6.
Additional 8 publications have been published so far.
The main models and methods being proposed and verified during the project REBELION are:
- Model capturing features of textual documents, which are important for detection of antisocial behaviour
- Method for multilingual detection of hate speech
- Method for sentiment classification of the content created at social networks
- Method for story-based fake news detection
- Model of comments’ sentiment in online discussions
- Model of contributing users in online discussions
- Method for troll detection
In addition, we are working on proposal and implemention of Monant platform, which serves for real-time and scalable web monitoring, mediating results exchange among models/methods and for providing public as well as experts users with end-user services.
As a part of the project REBELION, we cooperate with:
Master and PhD students
PhD students, who work on theses related to the project REBELION:
- Michal Farkaš
- Pooria Jafari
- Viera Maslej-Krešňáková
- Samuel Pecár
- Matúš Pikuliak
- Igor Stupavský
Additional 3 master students work on related master theses.