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Determining Top K Nodes in Social Networks using the Shapley Value

Suri, Rama N and Narahari, Y (2008) Determining Top K Nodes in Social Networks using the Shapley Value. In: Seventh International Joint Conference on Autonomous Agents and Multi-Agent Systems, AAMAS-2008, Estoril, Portugal, Estoril.

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Official URL: http://dl.acm.org/citation.cfm?id=1402911

Abstract

In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.

Item Type: Conference Paper
Keywords: Social Networks;co-authorship networks;Shapley value;ap- proximation algorithms
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 23 Sep 2011 09:34
Last Modified: 23 Sep 2011 09:34
URI: http://eprints.iisc.ernet.in/id/eprint/40671

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