Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model

Giuseppe De Martino and Serena Spina

Physica A: Statistical Mechanics and its Applications, 2015, vol. 438, issue C, 634-644

Abstract: We construct a news spreading model with a time dependent contact rate which generalizes the classical Susceptible–Infected model of epidemiology. In particular, we are interested on the time-dynamics of the sharing and diffusion process of news on the Internet. We focus on the counting process describing the number of connections to a given website, characterizing the cumulative density function of its inter-arrival times. Moreover, starting from the general form of the finite dimensional distribution of the process, we determine a formula for the time-variable rate of the connections and establish its relationship with the probability density function of the interarrival times. We finally show the effectiveness of our theoretical framework analyzing a real-world dataset, the Memetracker dataset, whose parameters characterizing the diffusion process are determined.

Keywords: News diffusion; Information diffusion models; Epidemiological models; Counting processes (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:438:y:2015:i:c:p:634-644

DOI: 10.1016/j.physa.2015.07.022

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