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Long Trend Dynamics in Social Media

Authors
  • Wang, Chunyan
  • Huberman, Bernardo A.
Type
Preprint
Publication Date
Dec 20, 2011
Submission Date
Sep 08, 2011
Identifiers
arXiv ID: 1109.1852
Source
arXiv
License
Yellow
External links

Abstract

A main characteristic of social media is that its diverse content, copiously generated by both standard outlets and general users, constantly competes for the scarce attention of large audiences. Out of this flood of information some topics manage to get enough attention to become the most popular ones and thus to be prominently displayed as trends. Equally important, some of these trends persist long enough so as to shape part of the social agenda. How this happens is the focus of this paper. By introducing a stochastic dynamical model that takes into account the user's repeated involvement with given topics, we can predict the distribution of trend durations as well as the thresholds in popularity that lead to their emergence within social media. Detailed measurements of datasets from Twitter confirm the validity of the model and its predictions.

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