Approach to automatic identification of terrorist and radical content in social networks messages
Andrey I. Kapitanov, Ilona I. Kapitanova, Vladimir M. Troyanovskiy, Vladimir F. Shangin, Nikolay O. Krylikov · 2018
Terrorist and radical groups of people use instant messengers and accounts on social networks to publish propaganda messages. Blocking such accounts is one of the most effective methods of countering them. To do this, analysts need to read and process a huge amount of information. In this paper we propose an approach based on machine learning that will automate the process of processing and classifying messages into radical and non-radical messages.