• DocumentCode
    1798909
  • Title

    Find you from your friends: Graph-based residence location prediction for users in social media

  • Author

    Dan Xu ; Peng Cui ; Wenwu Zhu ; Shiqiang Yang

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
  • fYear
    2014
  • fDate
    14-18 July 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    As a bridge between social media and physical space, location information will potentially make the internet smarter, and release the real power of social media to address the serious and significant problems in the real world. However, in terms of privacy and security, most of the users are unwilling to make their locations public. To address the problem, an algorithm is necessary to predict the users´ residence locations based on the public profiles. We define location propagation probability of users, leverage a semi-supervised learning algorithm, and introduce a novel method of location propagation to predict users´ residence locations based on users´ social relationships, textual and visual contents and a small amount of known users´ residence locations. The experimental results on a large scale real data set in Tencent Weibo demonstrate that our location propagation algorithm outperforms the state-of-the-art approaches in both accuracy and scalability.
  • Keywords
    Internet; learning (artificial intelligence); network theory (graphs); social networking (online); graph-based residence location prediction; location propagation algorithm; location propagation probability; physical space; public profile; semi-supervised learning algorithm; smart Internet; social media; social relationship; textual contents; user profiling; visual contents; Accuracy; Cities and towns; Media; Prediction algorithms; Security; User-generated content; Visualization; Social media; location prediction; social graph; user profiling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo (ICME), 2014 IEEE International Conference on
  • Conference_Location
    Chengdu
  • Type

    conf

  • DOI
    10.1109/ICME.2014.6890202
  • Filename
    6890202