Learning information diffusion model in a social network for predicting influence of nodes

@article{Kimura2011LearningID,
  title={Learning information diffusion model in a social network for predicting influence of nodes},
  author={Masahiro Kimura and Kazumi Saito and Kouzou Ohara and Hiroshi Motoda},
  journal={Intell. Data Anal.},
  year={2011},
  volume={15},
  pages={633-652}
}
We address the problem of estimating the parameters, from observed data in a complex social network, for an information diffusion model that takes time-delay into account, based on the popular independent cascade IC model. For this purpose we formulate the likelihood to obtain the observed data which is a set of time-sequence data of infected active nodes, and propose an iterative method to search for the parameters time-delay and diffusion that maximize this likelihood. We first show by using… CONTINUE READING

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