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Epidemiological modeling of online social network dynamics

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arxiv 1401.4208 v1 pith:OJPFEEXB submitted 2014-01-17 cs.SI physics.soc-ph

John Cannarella , Joshua A. Spechler This is my paper · ORCID
classification cs.SIphysics.soc-ph
keywords modelabandonmentrecoveryadoptionfacebookanalogousdatadynamics
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The last decade has seen the rise of immense online social networks (OSNs) such as MySpace and Facebook. In this paper we use epidemiological models to explain user adoption and abandonment of OSNs, where adoption is analogous to infection and abandonment is analogous to recovery. We modify the traditional SIR model of disease spread by incorporating infectious recovery dynamics such that contact between a recovered and infected member of the population is required for recovery. The proposed infectious recovery SIR model (irSIR model) is validated using publicly available Google search query data for "MySpace" as a case study of an OSN that has exhibited both adoption and abandonment phases. The irSIR model is then applied to search query data for "Facebook," which is just beginning to show the onset of an abandonment phase. Extrapolating the best fit model into the future predicts a rapid decline in Facebook activity in the next few years.

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Cited by 2 Pith papers

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  1. Influence Maximization in Temporal Networks with Persistent and Reactive Behaviors

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    cpSI-R, a temporal influence model with reactivation and reinforcement, is claimed to be monotone and submodular, but the proof assumes the properties it claims to prove.

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    cs.SI 2025-07 conditional novelty 3.0 of 10

    A survey that groups diffusion models into five categories and proposes a flowchart for choosing among them in temporal-network influence maximization.

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