Abstract
Online popularity has an enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems: the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and interevent time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.
Highlights
Online popularity has an enormous impact on opinions, culture, policy, and profits
Large scale, temporal analysis of the dynamics of online content popularity in two massive model systems: the Wikipedia and an entire country’s Web space
We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and interevent time
Summary
It is well documented that the statistical properties of these variables in the Web are very heterogeneous, with distributions characterized by fat tails roughly following power-law behavior [3,4,5,6] Such distributions have been explained with models based on the rich-getricher mechanism [7,8,9], but their validation from the point of view of the dynamical behavior is problematic, mainly due to the difficulty to gather relevant data. In order to gauge quantitatively the popularity of documents, we consider the number of hyperlinks pointing to a page (indegree k in the graph representation of the Web [3]) and the traffic s of the page, expressed by the number of clicks to it Given either of these two popularity proxies xt at time t, we study its logarithmic derivative 1⁄2Áx=xt 1⁄4 ðxt À xtÀ1Þ=xtÀ1, which represents the relative variation of the measure in the time unit
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