We are developing (i) Android and iOS smartphone applications and (ii) a browser extension. The smartphone applications and the browser extension perform real-time detection of fake news, not only providing warnings or early predictions of the likelihood of an article being fake news, but also highlighting the traits characteristic of fake news in the analyzed articles (such as typography, word choice, morphological and syntactical traits), and telling users about the manipulative strategies the highlighted traits are used for (such as creating fear, suggestion, rushing, rarity assumption psychology, blind group, false promise, etc.).
In addition to the rules-based applications, we are also developing an automatic fake news detector using artificial intelligence. We use positive and negative examples to develop a neural network that is capable of automatically detecting fake news.
Subproject leader
Prof. Dr. Csendes Tibor DSc
Department of Computational Optimization, University of Szeged
Participating researchers
Dr. Berend Gábor PhD
Department of Computer Algorithms and Artificial Intelligence, University of Szeged
Ficsor Tamás
Doctoral School of Computer Science, University of Szeged
Gencsi Mihály
Doctoral School of Computer Science, University of Szeged
Vörös Richárd
Computer Centre, University of Szeged
