Social capital: The power of influencers in networks

Karthik Subbian, Dhruv Sharma, Zhen Wen, Jaideep Srivastava

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

8 Scopus citations

Abstract

The problem of finding the influencers in social networks has been traditionally dealt in an optimization setting by finding the top-k nodes that has the maximum information spread in the network. These methods aim to find the influencers in a network through the process of information diffusion. However, none of these approaches model the individual social value generated by collaborations in these networks. Such social value is often the real motivation for which the nodes connect to each other. In this work, we propose a framework to compute this network social value using the concept of social capital, namely the amount of bonding and bridging connections in the network. We first compute the social capital value of the network and then allocate this network value to the nodes of the network. We establish the fairness of our allocation using several axioms of fairness. Our experiments on the real data sets show that the computed social capital is an excellent proxy for finding influencers and our approach outperforms several popular baselines.

Original languageEnglish (US)
Title of host publication12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1243-1244
Number of pages2
Volume2
StatePublished - Jan 1 2013
Event12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States
Duration: May 6 2013May 10 2013

Other

Other12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013
Country/TerritoryUnited States
CitySaint Paul, MN
Period5/6/135/10/13

Keywords

  • Collaborative Networks
  • Influencer Mining
  • Information Diffusion
  • Social Capital

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