Identification of extremist videos in online video sharing sites

Fu Tianjun, Chun Neng Huang, Chen Hsinchun

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

15 Scopus citations

Abstract

Web 2.0 has become an effective grassroots communication platform for extremists to promote their ideas, share resources, and communicate among each other. As an important component of Web 2.0, online video sharing sites such as YouTube and Google video have also been utilized by extremist groups to distribute videos. This study presented a framework for identifying extremist videos in online video sharing sites by using user-generated text content such as comments, video descriptions, and titles without downloading the videos. Text features including lexical features, syntactic features and content specific features were first extracted. Then Information Gain was used for feature selection, and Support Vector Machine was deployed for classification. The exploratory experiment showed that our proposed framework is effective for identifying online extremist videos, with the F-measure as high as 82%.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009
Pages179-181
Number of pages3
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009 - Dallas, TX, United States
Duration: Jun 8 2009Jun 11 2009

Publication series

Name2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009

Other

Other2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009
Country/TerritoryUnited States
CityDallas, TX
Period6/8/096/11/09

Keywords

  • Extremist video
  • Feature selection
  • Video classification
  • Video sharing
  • Web 2.0

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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