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Register a new userAnomalous popularity growth in social tagging ecosystems
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In social tagging systems, the diversity of tag vocabulary and the popularity of such tags continue to increase as they are exposed to selection pressure derived from our cognitive nature and cultural preferences. This is analogous to living ecosystems, where mutation and selection play a dominant role. Such population dynamism, which yields a scaling law, is mathematically modeled by a simple stochastic process---the Yule--Simon process, which describes how new words are introduced to the system and then grow. However, in actual web services, we have observed that a large fluctuation emerges in the popularity growth of individual tags that cannot be explained by the ordinary selection mechanism. We introduce a scaling factor to quantify the degree of the deviation in the popularity growth from the mean-field solution of the Yule--Simon process, and we discuss possible triggers of such anomalous popularity behavior.
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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 $alpha<2$, unlike preferential-attachment models), similar to those seen in empirical data.
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