On Detecting Online Radicalization and Extremism Using Natural Language Processing
Shynar Mussiraliyeva, Milana Bolatbek, Батырхан Омаров, Zhanar Medetbek, Gulshat Baispay, Ruslan Ospanov
Abstract
Due to the activity of terrorist propaganda on the Internet and social networks, as well as given the high dynamics of the emergence of new sites and accounts of extremist orientation, it is important to quickly detect content that demonstrates a tendency to extremism in the prevention of extremist and terrorist activities. This article is intended to explore the possibilities of automatic recognition of extremist content using machine learning from this point of view. This article is devoted to the application of machine learning methods for solving the problem of security, in part-countering terrorism and extremism using information from the Internet.