Branching Dynamics of Viral Information Spreading

Abstract

Despite its importance for rumors or innovations propagation, peer-to-peer collaboration, social networking or Marketing, the dynamics of information spreading is not well understood. Since the diffusion depends on the heterogeneous patterns of human behavior and is driven by the participants' decisions, its propagation dynamics shows surprising properties not explained by traditional epidemic or contagion models. Here we present a detailed analysis of our study of real Viral Marketing campaigns where tracking the propagation of a controlled message allowed us to analyze the structure and dynamics of a diffusion graph involving over 31,000 individuals. We found that information spreading displays a non-Markovian branching dynamics that can be modeled by a two-step Bellman-Harris Branching Process that generalizes the static models known in the literature and incorporates the high variability of human behavior. It explains accurately all the features of information propagation under the "tipping-point" and can be used for prediction and management of viral information spreading processes.

15 pages, 9 figures. Accepted in Physical Review E

References in corpus (4)

• Statistical physics of social dynamics
• Small But Slow World: How Network Topology and Burstiness Slow Down Spreading
• A message passing approach for general epidemic models
• Affinity Paths and Information Diffusion in Social Networks

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