Characterizing and modeling the dynamics of online popularity

TL;DR

This paper analyzes the temporal dynamics of online popularity using large-scale data from Wikipedia and a country's web space, revealing bursty, critical-like behavior and proposing a minimal model to explain these phenomena.

Contribution

It introduces a minimal model combining preferential attachment with exogenous shifts to accurately reproduce observed popularity dynamics.

Findings

Popularity exhibits fat-tailed distributions of magnitude and inter-event times.

The proposed model captures critical features of empirical popularity data.

Popularity dynamics are driven by both endogenous growth and exogenous shocks.

Abstract

Online popularity has 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 inter-event 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.