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|---|---|---|---|
| 001 | 668201 | ||
| 005 | 20231030042141.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\39425 | ||
| 035 | _aRU\TPU\network\39288 | ||
| 090 | _a668201 | ||
| 100 | _a20220629a2022 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aCH | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aMethod for Detecting Far-Right Extremist Communities on Social Media _fA. Yu. Karpova, A. O. Savelyev, S. A. Kuznetsov, A. D. Vilnin |
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| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References: 63 tit.] | ||
| 330 | _aFar-right extremist communities actively promote their ideological preferences on social media. This provides researchers with opportunities to study these communities online. However, to explore these opportunities one requires a way to identify the far-right extremists’ communities in an automated way. Having analyzed the subject area of far-right extremist communities, we identified three groups of factors that influence the effectiveness of the research work. These are a group of theoretical, methodological, and instrumental factors. We developed and implemented a unique algorithm of calendar-correlation analysis (CCA) to search for specific online communities. We based CCA on a hybrid calendar correlation approach identifying potential far-right communities by characteristic changes in group activity around key dates of events that are historically crucial to those communities. The developed software module includes several functions designed to automatically search, process, and analyze social media data. In the current paper we present a process diagram showing CCA’s mechanism of operation and its relationship to elements of automated search software. Furthermore, we outline the limiting factors of the developed algorithm. The algorithm was tested on data from the Russian social network VKontakte. Two experimental data sets were formed: 259 far-right communities and the 49 most popular (not far-right) communities. In both cases, we calculated the type II error for two mutually exclusive hypotheses—far-right affiliation and no affiliation. Accordingly, for the first sample, Я = 0.81. For the second sample, Я = 0.02. The presented CCA algorithm was more effective at identifying far-right communities belonging to the alt-right and Nazi ideologies compared to the neo-pagan or manosphere communities. We expect that the CCA algorithm can be effectively used to identify other movements within far-right extremist communities when an appropriate foundation of expert knowledge is provided to the algorithm. | ||
| 461 | _tSocial Sciences | ||
| 463 |
_tVol. 11, iss. 5 _v[200, 20 p.] _d2022 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _aonline radicalization | |
| 610 | 1 | _afar-right | |
| 610 | 1 | _aextremism | |
| 610 | 1 | _aterrorism | |
| 610 | 1 | _asocial media analytics | |
| 610 | 1 | _abig data | |
| 610 | 1 | _aweb mining | |
| 610 | 1 | _aрадикализация | |
| 610 | 1 | _aэкстремизм | |
| 610 | 1 | _aтерроризм | |
| 610 | 1 | _aсоциальные сети | |
| 610 | 1 | _aбольшие данные | |
| 701 | 1 |
_aKarpova _bA. Yu. _cphilosopher _cProfessor of Tomsk Polytechnic University, Doctor of Social Sciences _f1968- _gAnna Yurievna _2stltpush _3(RuTPU)RU\TPU\pers\32542 |
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| 701 | 1 |
_aSavelyev _bA. O. _cSpecialist in the field of informatics and computer technology _cEngineer of Tomsk Polytechnic University _f1987- _gAleksey Olegovich _2stltpush _3(RuTPU)RU\TPU\pers\31388 |
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| 701 | 1 |
_aKuznetsov _bS. A. _cspecialist in the field of information technology _cEngineer of Tomsk Polytechnic University _f1985- _gSergey Anatoljeich _2stltpush _3(RuTPU)RU\TPU\pers\47274 |
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| 701 | 1 |
_aVilnin _bA. D. _cSpecialist in the field of automation equipment and electronics _cThe Head of the Laboratory of Tomsk Polytechnic University _f1980- _gAlexander Daniilovich _2stltpush _3(RuTPU)RU\TPU\pers\45840 |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bШкола базовой инженерной подготовки _bОтделение социально-гуманитарных наук _h8033 _2stltpush _3(RuTPU)RU\TPU\col\23512 |
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа информационных технологий и робототехники _bОтделение информационных технологий _h7951 _2stltpush _3(RuTPU)RU\TPU\col\23515 |
| 801 | 2 |
_aRU _b63413507 _c20221026 _gRCR |
|
| 856 | 4 | _uhttp://earchive.tpu.ru/handle/11683/73246 | |
| 856 | 4 | _uhttps://doi.org/10.3390/socsci11050200 | |
| 942 | _cCF | ||