Dominance or Fair Play in Social Networks? A Model of Influencer Popularity Dynamics

This paper presents a data-driven mean-field approach to model the popularity dynamics of users seeking public attention, i.e., in- fluencers. We propose a novel analytical model that integrates individual activity patterns, expertise in producing viral content, exogenous events, and the platform’s role in visibility enhancement, ultimately determin- ing each influencer’s success. We analytically derive sufficient conditions for system ergodicity, enabling predictions of popularity distributions. A sensitivity analysis explores various system configurations, highlight- ing conditions favoring either dominance or fair play among influencers. Our findings offer valuable insights into the potential evolution of social networks towards more equitable or biased influence ecosystems.