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Influence limitation in multi-campaign social networks: A Shapley value based approach

Premm Raj, H and Narahari, Y (2012) Influence limitation in multi-campaign social networks: A Shapley value based approach. In: 2012 IEEE International Conference on Automation Science and Engineering (CASE), 20-24 Aug. 2012, Seoul.

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Official URL: http://dx.doi.org/10.1109/CoASE.2012.6386448

Abstract

We investigate the problem of influence limitation in the presence of competing campaigns in a social network. Given a negative campaign which starts propagating from a specified source and a positive/counter campaign that is initiated, after a certain time delay, to limit the the influence or spread of misinformation by the negative campaign, we are interested in finding the top k influential nodes at which the positive campaign may be triggered. This problem has numerous applications in situations such as limiting the propagation of rumor, arresting the spread of virus through inoculation, initiating a counter-campaign against malicious propaganda, etc. The influence function for the generic influence limitation problem is non-submodular. Restricted versions of the influence limitation problem, reported in the literature, assume submodularity of the influence function and do not capture the problem in a realistic setting. In this paper, we propose a novel computational approach for the influence limitation problem based on Shapley value, a solution concept in cooperative game theory. Our approach works equally effectively for both submodular and non-submodular influence functions. Experiments on standard real world social network datasets reveal that the proposed approach outperforms existing heuristics in the literature. As a non-trivial extension, we also address the problem of influence limitation in the presence of multiple competing campaigns.

Item Type: Conference Proceedings
Additional Information: Copyright of this article belongs to IEEE.
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Depositing User: Id for Latest eprints
Date Deposited: 15 Mar 2013 06:18
Last Modified: 15 Mar 2013 06:18
URI: http://eprints.iisc.ac.in/id/eprint/45976

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