An Empirical Study of the Diversity of Athletes’ Followers on Twitter

  • Ricardo Silveira
  • Giulio Iacobelli
  • Daniel Figueiredo
Part of the Studies in Computational Intelligence book series (SCI, volume 644)


The study of user diversity in online social networks is an important and ongoing research effort to better understand human behavior. This work takes a step in this direction by providing an empirical study of around 8,000 athletes divided into 13 categories and followed by 197 million users in Twitter. We propose a metric for follower diversity at the category level that factors the vast popularity difference between categories (e.g., soccer versus golf). Using this metric, we propose a measure for athlete heterogeneity based on the diversity of his/her followers. Our findings reveal that follower diversity is spread across two scales with the vast majority of users having very small diversity. We also find that athlete heterogeneity is inversely proportional to its number of followers. This indicates that very popular athletes are followed by users that (on average) do not follow other sports.



This work has been partially funded through research grants from the following Brazilian agencies: CNPq, CAPES and FAPERJ.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ricardo Silveira
    • 1
  • Giulio Iacobelli
    • 1
  • Daniel Figueiredo
    • 1
  1. 1.Department of Computer and System Engineering (PESC)Federal University of Rio de Janeiro (UFRJ)Rio de JaneiroBrazil

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