4.6 Review

Online Extremism Detection in Textual Content: A Systematic Literature Review

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 42384-42396

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3064178

Keywords

Social networking (online); Terrorism; Natural language processing; Classification algorithms; Text analysis; Government; Text mining; Extremism detection; radicalism detection; terrorism detection; artificial intelligence; machine learning; natural language processing; systematic literature review

Funding

  1. Deanship of Scientific Research, King Saud University, through the initiative of DSR Graduate Students Research Support (GSR)

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Social media networks are increasingly being utilized by extremist groups to spread radical ideologies and recruit supporters, making it a top priority for counter-terrorist agencies, technology companies, and governments to identify extremist content and accounts. A systematic literature review of studies published between 2015 and 2020 revealed challenges, technical pitfalls, and opportunities for improving understanding and direction of online extremism. This critical analysis contributes to the growing field of research on online extremism.
Social media networks such as Twitter, Facebook, YouTube, blogs, and discussion forums are becoming powerful tools that extremist groups use to disseminate radical ideologies and propaganda, and to recruit people to their cause. Identifying extremist social media content and profiles is a top priority for counter-terrorist agencies, technology companies, and governments. The main objective of this paper is to provide a better understanding of the definition of extremism, and a detailed review of the current research regarding online extremism in text. To identify gaps in the literature, a systematic literature review (SLR) of 45 studies published between 2015 and 2020 was undertaken, which revealed challenges, technical pitfalls in previous studies, and opportunities for extending and improving prior results in meaningful ways. The systematic review indicates the need for better understanding of the landscape and directions of the online extremism. This study offers a critical analysis of the new area of research.

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