Predicting retweet count using visual cues

  • Authors:
  • Ethem F. Can;Hüseyin Oktay;R. Manmatha

  • Affiliations:
  • UMass, Amherst, MA, USA;UMass, Amherst, MA, USA;UMass, Amherst, MA, USA

  • Venue:
  • Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
  • Year:
  • 2013

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Abstract

Social media platforms allow rapid information diffusion, and serve as a source of information to many of the users. Particularly, in Twitter information provided by tweets diffuses over the users through retweets. Hence, being able to predict the retweet count of a given tweet is important for understanding and controlling information diffusion on Twitter. Since the length of a tweet is limited to 140 characters, extracting relevant features to predict the retweet count is a challenging task. However, visual features of images linked in tweets may provide predictive features. In this study, we focus on predicting the expected retweet count of a tweet by using visual cues of an image linked in that tweet in addition to content and structure-based features.