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Conference Paper: Combining intensification and diversification to maximize the propagation of social influence

TitleCombining intensification and diversification to maximize the propagation of social influence
Authors
Issue Date2013
PublisherIEEE. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000104
Citation
The 2013 IEEE International Conference on Communications (ICC 2013), Budapest, Hungary, 9-13 June 2013. In IEEE International Conference on Communications, 2013, p. 2995-2999 How to Cite?
AbstractIn this paper we consider the influence maximization problem in social networks, and propose an Int-Div heuristic to solve it. Motivated by the concepts of intensification and diversification in optimization problems, Int-Div accounts for both of these two concepts to estimate the social influence, and selects nodes based on marginal influence increment. It is applicable to the two widely used diffusion models, namely, the Linear Threshold Model and the Independent Cascade Model. The proposed strategy is evaluated through experiments on a collaboration network and a who-trust-whom online social network, respectively, and compared with several existing heuristics, namely, the pure greedy algorithm, the centrality-based scheme, the single discount and the degree discount heuristics. We find that our proposed strategy offers better performance than the centrality-based scheme, the single discount and the degree discount heuristics, while achieving approximately the same performance as the greedy algorithm. The computational load is dramatically lower than the greedy heuristic.
DescriptionIEEE ICC 2013 - Communication Software and Services Symposium
Session CSS-03 - Applications (Panorama IV)
Persistent Identifierhttp://hdl.handle.net/10722/191607
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorFan, Xen_US
dc.contributor.authorLi, VOKen_US
dc.date.accessioned2013-10-15T07:14:36Z-
dc.date.available2013-10-15T07:14:36Z-
dc.date.issued2013en_US
dc.identifier.citationThe 2013 IEEE International Conference on Communications (ICC 2013), Budapest, Hungary, 9-13 June 2013. In IEEE International Conference on Communications, 2013, p. 2995-2999en_US
dc.identifier.isbn978-1-4673-3122-7-
dc.identifier.issn1550-3607-
dc.identifier.urihttp://hdl.handle.net/10722/191607-
dc.descriptionIEEE ICC 2013 - Communication Software and Services Symposium-
dc.descriptionSession CSS-03 - Applications (Panorama IV)-
dc.description.abstractIn this paper we consider the influence maximization problem in social networks, and propose an Int-Div heuristic to solve it. Motivated by the concepts of intensification and diversification in optimization problems, Int-Div accounts for both of these two concepts to estimate the social influence, and selects nodes based on marginal influence increment. It is applicable to the two widely used diffusion models, namely, the Linear Threshold Model and the Independent Cascade Model. The proposed strategy is evaluated through experiments on a collaboration network and a who-trust-whom online social network, respectively, and compared with several existing heuristics, namely, the pure greedy algorithm, the centrality-based scheme, the single discount and the degree discount heuristics. We find that our proposed strategy offers better performance than the centrality-based scheme, the single discount and the degree discount heuristics, while achieving approximately the same performance as the greedy algorithm. The computational load is dramatically lower than the greedy heuristic.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000104-
dc.relation.ispartofIEEE International Conference on Communicationsen_US
dc.rightsIEEE International Conference on Communications. Copyright © IEEE.-
dc.rights©2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleCombining intensification and diversification to maximize the propagation of social influenceen_US
dc.typeConference_Paperen_US
dc.identifier.emailFan, X: xgfan@eee.hku.hken_US
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.authorityLi, VOK=rp00150en_US
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros225541en_US
dc.identifier.spage2995-
dc.identifier.epage2999-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 131114-

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