Detection of Violent Extremists in Social Media

Hamidreza Alvari, Soumajyoti Sarkar, Paulo Shakarian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The ease of use of the Internet has enabled violent extremists such as the Islamic State of Iraq and Syria (ISIS) to easily reach large audience, build personal relationships and increase recruitment. Social media are primarily based on the reports they receive from their own users to mitigate the problem. Despite efforts of social media in suspending many accounts, this solution is not guaranteed to be effective, because not all extremists are caught this way, or they can simply return with another account or migrate to other social networks. In this paper, we design an automatic detection scheme that using as little as three groups of information related to usernames, profile, and textual content of users, determines whether or not a given username belongs to an extremist user. We first demonstrate that extremists are inclined to adopt usernames that are similar to the ones that their like-minded have adopted in the past. We then propose a detection framework that deploys features which are highly indicative of potential online extremism. Results on a real-world ISIS-related dataset from Twitter demonstrate the effectiveness of the methodology in identifying extremist users.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 2nd International Conference on Data Intelligence and Security, ICDIS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages43-47
Number of pages5
ISBN (Electronic)9781728120805
DOIs
StatePublished - Jun 2019
Event2nd International Conference on Data Intelligence and Security, ICDIS 2019 - South Padre Island, United States
Duration: Jun 28 2019Jun 30 2019

Publication series

NameProceedings - 2019 2nd International Conference on Data Intelligence and Security, ICDIS 2019

Conference

Conference2nd International Conference on Data Intelligence and Security, ICDIS 2019
CountryUnited States
CitySouth Padre Island
Period6/28/196/30/19

Keywords

  • Extremists
  • Feature Engineering
  • Social media

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Alvari, H., Sarkar, S., & Shakarian, P. (2019). Detection of Violent Extremists in Social Media. In Proceedings - 2019 2nd International Conference on Data Intelligence and Security, ICDIS 2019 (pp. 43-47). [8855278] (Proceedings - 2019 2nd International Conference on Data Intelligence and Security, ICDIS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDIS.2019.00014