Competition-induced criticality in a model of meme popularity

By J. P. Gleeson, Jonathan A. Ward, Kevin P. O'Sullivan, William T. Lee. 2013

138 citations recorded by the source corpus.

Heavy-tailed distributions of meme popularity occur naturally in a model of meme diffusion on social networks. Competition between multiple memes for the limited resource of user attention is identified as the mechanism that poises the system at criticality. The popularity growth of each meme is described by a critical branching process, and asymptotic analysis predicts power-law distributions of popularity with very heavy tails (exponent α<2, unlike preferential-attachment models), similar to those seen in empirical data.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

How algorithmic popularity bias hinders or promotes quality (2017, background): “pularity in the presence of competition among networked agents with limited attention, irrespective of quality [34], and the popularity of memes follows a power-law distribution with very heavy tails [13]. Mechanisms such as unfriending and triadic closure facilitate the formation of homogeneous \ec”
Limited individual attention and online virality of low-quality information (2017, background): “[24, 23] formalized this model as a critical branching process, predicting that the popularity of memes follows a power-law distribution with very heavy tails.”