Hybrid Approach for Bots Detection in Social Networks Based on Topological, Textual and Statistical Features

被引：0

作者：

Vitkova, Lidia ^{[1
]}

Kotenko, Igor ^{[1
]}

Kolomeets, Maxim ^{[1
]}

Tushkanova, Olga ^{[1
]}

Chechulin, Andrey ^{[1
]}

机构：

[1] Russian Acad Sci, St Petersburg Inst Informat & Automat, 14 Th Liniya,39, St Petersburg 199178, Russia

来源：

PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19) | 2020年 / 1156卷

基金：

俄罗斯科学基金会;

关键词：

Social network analysis; Visual analysis; Data mining; Statistics; Bots detection; PROTECTION;

D O I：

10.1007/978-3-030-50097-9_42

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper presents a hybrid approach to social network analysis for obtaining information on suspicious user profiles. The offered approach is based on integration of statistical techniques, data mining and visual analysis. The advantage of the proposed approach is that it needs limited kinds of social network data ("likes" in groups and links between users) which is often in open access. The results of experiments confirming the applicability of the proposed approach are outlined.

引用

页码：412 / 421

页数：10

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