• DocumentCode
    3156402
  • Title

    Content Mining of Microblogs

  • Author

    Cingiz, M. Ozgur ; Diri, B.

  • Author_Institution
    Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey
  • fYear
    2012
  • fDate
    26-29 Aug. 2012
  • Firstpage
    835
  • Lastpage
    838
  • Abstract
    Emergence of Web 2.0, internet users can share their contents with other users using social networks. In this paper microbloggers´ contents are evaluated with respect to how they reflect their categories. Migrobloggers´ category information, which is one of the four categories that are economy sport, entertainment or technology, is taken from wefollow.com application. 2105 RSS news feeds, whose category labels are same with microbloggers´ contributions, are used as training data for classification. In this study two types of users´ contributions are taken as test data. These users are normal micro loggers and bots. Classification results show that bots provide more categorical content than normal users.
  • Keywords
    Internet; content management; data mining; pattern classification; social networking (online); 2105 RSS news feeds; Internet users; Web 2.0; classification; content mining; economy sport; entertainment; microblogs; migroblogger category information; social networks; technology; training data; wefollow.com application; Educational institutions; Entertainment industry; Feeds; Support vector machine classification; Text categorization; Training; classification; content mining; data mining; microblogging; social web mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4673-2497-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2012.151
  • Filename
    6425656