Extremist text detection in social web


Смирнов И. В. Девяткин Д. А. Суворова (Ананьева) М. И.


Online or cyber extremism is one of the critical problem for the security of Russia and other countries as social web is widely used for radical activity and propaganda. This paper considers the problem of extremist text detection in Russian social media. We propose models and methods for identification of extremist text in Russian, which apply deep linguistic parsing and statistical processing of texts. We also present the dataset of terrorist, religious hate, racism and other radical texts in Russian and results of experiments on this dataset. It was shown, that low-dimensional psycholinguistic and semantic features of texts allow detecting extremist texts with quite good performance while lexical features allow recognizing topics of the detected extremist texts.

Внешние ссылки

DOI: http://dx.doi.org/10.33965/wbc2019_201908L041

PDF в электронной библиотеке IADIS (англ.): http://www.iadisportal.org/digital-library/mdownload/extremist-text-detection-in-social-web

РИНЦ: https://elibrary.ru/item.asp?id=41690871

Публикации ВШЭ: https://publications.hse.ru/chapters/314143478

Ссылка при цитировании

Devyatkin D., Smirnov I., Solovyev F., Suvorova M., Chepovskiy A. Extremist text detection in social web // Proceedings of the Multi Conference on Computer Science and Information Systems, MCCSIS 2019. Porto 2019, Pages 344-350.