An advisory method for BBS users and evaluation of BBS comments

Yu Ichifuji, Susumu Konno, Hideaki Sone

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

Recently, BBS has a problem which threatens the safety of BBS community: vandalism comments. Such comments occur by fault and by misunderstanding. Thus, showing the probability of becoming vandalism comment can reduce such vandalism comments. We proposed a method to calculate the probability of becoming vandalism comment. This method classified each comment into "Normal comment", "Vandalism comment" or "Flaming comment" using word and pair of words based on Bayesian theorem. As the result of experiment, we showed that proposed method could classify normal comments into normal comment class with 64.7% accuracy and vandalism or flaming comments into vandalism comment class with 85.4% accuracy.

Original languageEnglish
Pages (from-to)218-224
Number of pages7
JournalProcedia - Social and Behavioral Sciences
Volume2
Issue number1
DOIs
Publication statusPublished - 2010 Aug 2
Event1st International Conference on Security Camera Network, Privacy Protection and Community Safety 2009, SPC2009 - Kiryu, Japan
Duration: 2009 Oct 282009 Oct 30

Keywords

  • Bayesian theorem
  • Bulletin Board System (BBS)
  • Morphological analysis

ASJC Scopus subject areas

  • Social Sciences(all)
  • Psychology(all)

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