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Title:
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EXTREMIST TEXT DETECTION IN SOCIAL WEB |
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Author(s):
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Dmitry Devyatkin, Ivan Smirnov, Fyodor Solovyev, Margarita Suvorova and Andrey Chepovskiy |
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ISBN:
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978-989-8533-90-6 |
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Editors:
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Piet Kommers and Guo Chao Peng |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Cyber Extremism, Radical Texts Detection, Topic Identification, Psycholinguistic Features, Semantics, Extremist Lexis |
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Type:
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Full Paper |
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First Page:
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344 |
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Last Page:
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350 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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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. |
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