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An Approach for Hate Groups Detection in Facebook

  • I-Hsien TingEmail author
  • Hsing-Miao Chi
  • Jyun-Sing Wu
  • Shyue-Liang Wang
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

In recent years, with the growth of social networking websites, users are very active in these platforms and a large amount of data is aggregated. Among those social networking websites, Facebook is the most popular one that has most users. However, in Facebook, the existence of Hate Groups is a very critical issue with the problem of abusing. Therefore, many researchers are devoting themselves to detecting the potential hate groups, using the techniques of social networks analysis and web mining. In this paper, we will propose an approach based on the techniques of social networks analysis and web mining to detect the potential hate groups. The data from Facebook are being processed. In the research, hate groups for 3C are selected as the training data. The social network structures and keywords of these groups will be treated as the features which will be used for discovering the potential hate groups in Facebook.

Keywords

Facebook Hate groups Social networks analysis Web mining 

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • I-Hsien Ting
    • 1
    Email author
  • Hsing-Miao Chi
    • 1
  • Jyun-Sing Wu
    • 1
  • Shyue-Liang Wang
    • 1
  1. 1.Department of Information ManagementNational University of KaohsiungKaohsiungTaiwan, R.O.C

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