A survey of extremism online content analysis and prediction techniques in twitter based on sentiment analysis

Zouheir Trabelsi, Firas Saidi, Eswari Thangaraj, T. Veni

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Nowadays, extremist organizations use social networks, such as Twitter, to flourish their dark activities. Usually, to polarize new members, these organizations attempt to share their radical propaganda by posting tweets. Practically, Sentiment Analysis (SA) techniques are widely used to classify the polarity of these extremist tweets, to derive appropriate conclusions for decision-making purposes, and to make valuable predictions about future violent and terrorist events. To study the influence of social networks-based malicious activities on human security and safety, this paper surveyed different Machine and Deep Learning based techniques used for Tweets SA, and discussed their strengths and weaknesses and recent trends in the field. Furthermore, the conducted survey work highlighted promising key areas and potential challenges that require further consideration to implement more effective methods to combat extremism in online social networks.

Original languageEnglish
Pages (from-to)221-248
Number of pages28
JournalSecurity Journal
Volume36
Issue number2
DOIs
Publication statusPublished - Jun 2023

Keywords

  • Machine learning (ML)
  • Opinion mining (OM)
  • Social networks extremism
  • Twitter sentiment analysis (TSA)

ASJC Scopus subject areas

  • Safety Research
  • Strategy and Management
  • Law

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