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Network Effects on Tweeting

  • Jake T. Lussier
  • Nitesh V. Chawla
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6926)

Abstract

Online social networks (OSNs) have created new and exciting ways to connect and share information. Perhaps no site has had a more profound effect on information exchange than Twitter.com. In this paper, we study large-scale graph properties and lesser-studied local graph structures of the explicit social network and the implicit retweet network in order to better understand the relationship between socialization and tweeting behaviors. In particular, we first explore the interplay between the social network and user tweet topics and offer evidence that suggests that users who are close in the social graph tend to tweet about similar topics. We then analyze the implicit retweet network and find highly unreciprocal links and unbalanced triads. We also explain the effects of these structural patterns on information diffusion by analyzing and visualizing how URLs tend to be tweeted and retweeted. Finally, given our analyses of the social network and the retweet network, we provide some insights into the relationships between these two networks.

Keywords

Data mining social networks information diffusion 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jake T. Lussier
    • 1
  • Nitesh V. Chawla
    • 1
  1. 1.Interdisciplinary Center for Network Science and Applications (iCeNSA)University of Notre DameNotre DameUSA

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