Banzhaf index for influence maximization

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Abstract

Social media has changed the way people communicate with each other and has brought people together. Enterprises are increasingly using it as a medium for marketing activities. However, due to the size of these networks, marketers often look for key customers (influencers) to drive the campaign to the community. In this paper, we take a game theoretic approach to identify key influencers in a network. We begin with defining coalition games to model the social network and then use the concept of Banzhaf index to measure the utility of each user to the coalition. We further extend this concept towards identification of influencers and compare the resulting algorithm against existing works on influence maximization on several datasets. Improvements are observed.

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Srinivasan, B. V., & Kumar, A. S. (2015). Banzhaf index for influence maximization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9471, pp. 261–273). Springer Verlag. https://doi.org/10.1007/978-3-319-27433-1_18

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