• DocumentCode
    3585428
  • Title

    Retweet Behavior Prediction in Twitter

  • Author

    Dongxu Huang ; Jing Zhou ; Dejun Mu ; Feisheng Yang

  • Author_Institution
    Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
  • Volume
    2
  • fYear
    2014
  • Firstpage
    30
  • Lastpage
    33
  • Abstract
    Retweet, as a main way to spread information in twitter, has been researched in a number of works. Recently research focuses on analyzing the factors of retweet behavior. However, the prediction on retweet behavior is a new challenge which is not well studied in the past. A basic fact is that different people are interested in different kinds of tweets, and they will retweet tweets which they are interested in. First, we collect tweets of different categories from valid account of famous news media as learning corpus. Second, in order to discover user interests, we classify user tweets into different categories by Bayes model. Finally, we measure user interests on tweets of different categories, and predict retweet behavior by interest measurement. This paper extends the previous study on retweet behavior, and we predict user retweet behavior as well as infer user interests. Experiment shows Bayes model has good performance on classifying tweets, and our algorithm achieves more precision than others.
  • Keywords
    Bayes methods; human factors; social networking (online); Bayes model; Twitter; news media; user retweet behavior prediction; Algorithm design and analysis; Autoregressive processes; Classification algorithms; Media; Prediction algorithms; Predictive models; Social network services; Bayes model; retweet; retweet bahavior prediction; twitter; user interests;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
  • Print_ISBN
    978-1-4799-7004-9
  • Type

    conf

  • DOI
    10.1109/ISCID.2014.187
  • Filename
    7081930