Tweet! – And I Can Tell How Many Followers You Have

  • Christine Klotz
  • Annie Ross
  • Elizabeth Clark
  • Craig Martell
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 265)

Abstract

Follower relations are the new currency in the social web. User-generated content plays an important role for the tie formation process. We report an approach to predict the follower counts of Twitter users by looking at a small amount of their tweets. We also found a pattern of textual features that demonstrates the correlation between Twitter specific communication and the number of followers. Our study is a step forward in understanding relations between social behavior and language in online social networks.

Keywords

Twitter follower user characteristics text mining n-grams Naïve Bayes tf-idf online social networks 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Christine Klotz
    • 1
  • Annie Ross
    • 2
  • Elizabeth Clark
    • 3
  • Craig Martell
    • 4
  1. 1.FernUniversität in Hagen, Fakultät für Mathematik und InformatikHagenGermany
  2. 2.Colorado State UniversityFort CollinsUSA
  3. 3.Middlebury CollegeMiddleburyUSA
  4. 4.Department of Computer ScienceNaval Postgraduate SchoolMontereyUSA

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