• DocumentCode
    3158881
  • Title

    Analyzing User Retweet Behavior on Twitter

  • Author

    Zhiheng Xu ; Qing Yang

  • Author_Institution
    Inst. of Autom., Beijing, China
  • fYear
    2012
  • fDate
    26-29 Aug. 2012
  • Firstpage
    46
  • Lastpage
    50
  • Abstract
    This paper provides a deep analysis of user retweet behavior on Twitter. While previous works about analyzing retweet have mainly focused on predicting the retweetability of each tweet, they lacked interpretations at an individual level. In this paper, we perform a general analysis of retweet behavior from the perspective of individual users. Specifically, we train a prediction model to forecast whether a tweet will be retweeted by a given user, leveraging four different types of features: social-based, content-based, tweet-based and author-based features. By performing “leave-one-feature-out” comparisons, we identify factors that are strongly associated with user retweet behavior.
  • Keywords
    behavioural sciences computing; social networking (online); Twitter; author-based feature; content-based feature; prediction model; social-based feature; tweet-based feature; user retweet behavior analysis; Feature extraction; Logistics; Predictive models; Support vector machines; Training; Twitter; Twitter; retweet behavior; social media;
  • 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.2012.18
  • Filename
    6425786