Characterizing topic-specific hashtag cascade in twitter based on distributions of user influence

  • Authors:

  • Geerajit Rattanaritnont;Masashi Toyoda;Masaru Kitsuregawa

  • Affiliations:

  • The University of Tokyo, Tokyo, Japan;The University of Tokyo, Tokyo, Japan;The University of Tokyo, Tokyo, Japan

  • Venue:
  • APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
  • Year:
  • 2012

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Abstract

As online social networks become extremely popular in these days, people communicate and exchange information for various purposes. In this paper, we investigate patterns of information diffusion and behaviors of participating users in Twitter, which would be useful to verify the effectiveness of marketing and publicity campaigns. We characterize Twitter hashtag cascades corresponding to different topics by exploiting distributions of user influence; cascade ratio and tweet ratio. The cascade ratio indicates an ability of users to spread information to their neighborhoods, and the tweet ratio measures how much each user participates in each topic. We examined these two measures on a real Twitter dataset and found three major diffusion patterns over four topics.