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Method of Identification of Extremist Texts in the Russian Language Based on the Fuzzy Logic

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10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions - ICSCCW-2019 (ICSCCW 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1095))

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Abstract

The article describes the author’s methodology of the study of the Russian language texts in order to identify their extremist orientation. This method is based on the fuzzy logic. The identified problems in solving the task are indicated. Then the description of the method is presented. There are also main points of fuzzy logic and soft computing tools used in the development of the method. We also determined a set of indicators consisting of four groups: (1) markers of extremist orientation (by types of extremism); (2) markers of linguistic manipulation; (3) indicators of verbal aggression; (4) scientific and journalistic terms. There is quantitative and qualitative characterization for each group of indicators. After that, the process of formation of the evaluation of the studied text on the extremist orientation is described in detail. This process is described on the basis of the system being fuzzy-logical conclusions, called fuzzy multilevel [0,1] – classifiers.

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References

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Author information

Authors and Affiliations

  1. Private Educational Institution of Higher Education “SOUTHERN UNIVERSITY (IMBL)”, Rostov-on-Don, Russia

    Olga Vitchenko & Yuri Dashko

  2. Rostov State University of Economics, Rostov-on-Don, Russia

    Evgeny Tishchenko & Lyudmila Sakharova

Authors
  1. Olga Vitchenko
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  2. Yuri Dashko
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  3. Evgeny Tishchenko
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  4. Lyudmila Sakharova
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Corresponding author

Correspondence to Lyudmila Sakharova .

Editor information

Editors and Affiliations

  1. Joint MBA Program, Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Rafik A. Aliev

  2. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  4. Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA

    Mo Jamshidi

  5. Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Mustafa B. Babanli

  6. Department of Mechatronics, Near East University, Nicosia, Turkey

    Fahreddin M. Sadikoglu

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Vitchenko, O., Dashko, Y., Tishchenko, E., Sakharova, L. (2020). Method of Identification of Extremist Texts in the Russian Language Based on the Fuzzy Logic. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M., Sadikoglu, F. (eds) 10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions - ICSCCW-2019. ICSCCW 2019. Advances in Intelligent Systems and Computing, vol 1095. Springer, Cham. https://doi.org/10.1007/978-3-030-35249-3_33

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