Prediction of Information Diffusion Probabilities for Independent Cascade Model

Authors:
Kazumi Saito;Ryohei Nakano;Masahiro Kimura
Affiliations:
School of Administration and Informatics, University of Shizuoka, Shizuoka, Japan 422-8526;Department of Computer Science and Engineering, Nagoya Institute of Technology, Nagoya, Japan 466---8555;Department of Electronics and Informatics, Ryukoku University, Otsu, Shiga, Japan 520-2194
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Year:
2008

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Abstract

We address a problem of predicting diffusion probabilities in complex networks. As one approach to this problem, we focus on the independent cascade (IC) model, and define the likelihood for information diffusion episodes, where an episode means a sequence of newly active nodes. Then, we present a method for predicting diffusion probabilities by using the EM algorithm. Our experiments using a real network data set show the proposed method works well.