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Explaining the emergence of online popularity through a model of information diffusion


This paper proposes a new formal modeling approach to popularity dynamics based on a generic notion of message propagation within society. The approach is demonstrated with two original models of information diffusion. These are a branching model of popularity and a epidemic model of popularity. The first is based on the principles of a branching process, while the second emulates an epidemic equation with a specific infection rate. This allows us to consider the replication phenomena on information diffusion. The approach is validated using a very large dataset collected online that involves keywords in blogs and hashtags on Twitter. Our main results point to an overall good fit of both models, both when the process of popularity grows and when it decays. This is due to endogenous information transfer, as in an epidemic process, but also when the process is initially triggered by an external event. Overall, on balance, our models confirm that popularity builds through message diffusion, which is of the multiplicative kind.

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  1. Therefore, particular conditions of message propagation within the social network are not considered in this paper. Moreover, in our case study particular topologies of the network are not considered either.

  2. This branching model is partially inspired by the resolution steps presented in Sornette et al. (2004).


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Correspondence to Jorge Louçã.

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Fonseca, A., Louçã, J. Explaining the emergence of online popularity through a model of information diffusion. Comput Math Organ Theory 24, 169–187 (2018).

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  • Information diffusion
  • Online social media
  • Popularity dynamics
  • Branching models
  • Epidemic models