A Survey on Computational Propaganda Detection

A Survey on Computational Propaganda Detection

Giovanni Da San Martino, Stefano Cresci, Alberto Barrón-Cedeño, Seunghak Yu, Roberto Di Pietro, Preslav Nakov

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Survey track. Pages 4826-4832. https://doi.org/10.24963/ijcai.2020/672

Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda. They exploit the anonymity of the Internet, the micro-profiling ability of social networks, and the ease of automatically creating and managing coordinated networks of accounts, to reach millions of social network users with persuasive messages, specifically targeted to topics each individual user is sensitive to, and ultimately influencing the outcome on a targeted issue. In this survey, we review the state of the art on computational propaganda detection from the perspective of Natural Language Processing and Network Analysis, arguing about the need for combined efforts between these communities. We further discuss current challenges and future research directions.
Keywords:
Natural Language Processing: general
Machine Learning: general