TURank: Twitter User Ranking Based on User-Tweet Graph Analysis

  • Yuto Yamaguchi
  • Tsubasa Takahashi
  • Toshiyuki Amagasa
  • Hiroyuki Kitagawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6488)


In this paper, we address the problem of finding authoritative users in a micro-blogging service, Twitter, which is one of the most popular micro-blogging services [1]. Twitter has been gaining a public attention as a new type of information resource, because an enormous number of users transmit diverse information in real time. In particular, authoritative users who frequently submit useful information are considered to play an important role, because useful information is disseminated quickly and widely. To identify authoritative users, it is important to consider actual information flow in Twitter. However, existing approaches only deal with relationships among users. In this paper, we propose TURank (Twitter User Rank), which is an algorithm for evaluating users’ authority scores in Twitter based on link analysis. In TURank, users and tweets are represented in a user-tweet graph which models information flow, and ObjectRank is applied to evaluate users’ authority scores. Experimental results show that the proposed algorithm outperforms existing algorithms.


Edge Weight Authority Score Link Structure Post Edge User Account 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yuto Yamaguchi
    • 1
  • Tsubasa Takahashi
    • 1
  • Toshiyuki Amagasa
    • 1
    • 2
  • Hiroyuki Kitagawa
    • 1
    • 2
  1. 1.Graduate School of Systems and Information EngineeringUniversity of TsukubaJapan
  2. 2.Center for Computational SciencesUniversity of TsukubaJapan

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