Influence maximization in social networks: An Ising-model-based approach

Shihuan Liu, Lei Ying, Srinivas Shakkottai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

38 Scopus citations

Abstract

The past few years have seen increasing interest in understanding social networks as a medium for community interaction. A major challenge has been to understand various fundamental properties of social networks that form the basis for the formation and propagation of opinions across such networks. The main hurdle has been the absence of plausible models that specify the correlations between different members of a social network, which could then be used for algorithm design. This paper studies an influence maximization problem using an Ising-model-based approach. We first validate the credibility of the ferromagnetic Ising model in predicting opinion formation in social networks using cosponsorship data from the US Senate proceedings. We then develop a greedy placement algorithm that can efficiently find an appropriate subset of network members, "bribing" whom can efficiently propagate a particular opinion in the network. We use simulations to confirm the effectiveness of the greedy placement algorithm.

Original languageEnglish (US)
Title of host publication2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
Pages570-576
Number of pages7
DOIs
StatePublished - 2010
Externally publishedYes
Event48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010 - Monticello, IL, United States
Duration: Sep 29 2010Oct 1 2010

Publication series

Name2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010

Other

Other48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
Country/TerritoryUnited States
CityMonticello, IL
Period9/29/1010/1/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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