• DocumentCode
    119470
  • Title

    Forum-Oriented Research on Water Army Detection for Bursty Topics

  • Author

    Huijie Xu ; Wandong Cai ; Guirong Chen

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2014
  • fDate
    6-8 Aug. 2014
  • Firstpage
    78
  • Lastpage
    82
  • Abstract
    Water army means a special group of online users who get paid for posting comments and new threads or articles on different online communities and websites for some hidden purposes. Due to the fact that the nature of the posting behavior of water army is not fully and understood, the driving force detection of the bursty topic for web forum is still a difficult problem to solve. According to the analysis of bursty topics evolution and the posting behavior of water army, it is found that the topics driven by water army exhibit the characteristics different from general topics in their latency stage. Based on this discovery, the paper proposes a novel bursty topic classification algorithm, based on SVM active learning, which transforms the water army detection issue to a SVM-based classification decision issue. The experimental results show that the proposed algorithm has higher detection accuracy and detection efficiency.
  • Keywords
    Web sites; learning (artificial intelligence); pattern classification; support vector machines; text analysis; SVM active learning; SVM-based classification decision issue; Web forum; Websites; bursty topic classification algorithm; driving force detection; forum-oriented research; hidden purposes; latency stage; online communities; online users; water army detection; Accuracy; Algorithm design and analysis; Classification algorithms; Indexes; Support vector machines; Training; Water; active learning; bursty topic; water army detection; web forum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Architecture, and Storage (NAS), 2014 9th IEEE International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/NAS.2014.18
  • Filename
    6923161