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Banzhaf Index for Influence Maximization

  • Balaji Vasan SrinivasanEmail author
  • Arava Sai Kumar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9471)

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.

Keywords

Social Network Centrality Measure Collaboration Network Marginal Contribution Coalition Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Adobe Research Big Data Intelligence LabsBangaloreIndia
  2. 2.Adobe Systems India Private LimitedBangaloreIndia

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