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Conference Paper: An analytical model for the propagation of social influence

TitleAn analytical model for the propagation of social influence
Authors
KeywordsSocial Network Intelligence
Social Influence Propagation
Analytical Model
Markov Chain
Issue Date2013
PublisherIEEE Computer Society. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001411
Citation
The 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Atlanta, GA., 18-20 November 2013. In Conference Proceedings, 2013, p. 1-8 How to Cite?
AbstractStudying the propagation of social influence is critical in the analysis of online social networks. While most existing work focuses on the expected number of users influenced, the detailed probability distribution of users influenced is also significant. However, determining the probability distribution of the final influence propagation state is difficult. Monte-Carlo simulations may be used, but are computationally expensive. In this paper, we develop an analytical model for the influence propagation process in online social networks based on discretetime Markov chains, and deduce a closed-form equation for the n-step transition probability matrix. We show that given any initial state, the probability distribution of the final influence propagation state may be easily obtained from a matrix product. This provides a powerful tool to further understand social influence propagation.
DescriptionSession 1: Web Intelligence Foundations I
Persistent Identifierhttp://hdl.handle.net/10722/191603
ISBN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFan, Xen_US
dc.contributor.authorNiu, Gen_US
dc.contributor.authorLi, VOKen_US
dc.date.accessioned2013-10-15T07:14:35Z-
dc.date.available2013-10-15T07:14:35Z-
dc.date.issued2013en_US
dc.identifier.citationThe 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Atlanta, GA., 18-20 November 2013. In Conference Proceedings, 2013, p. 1-8en_US
dc.identifier.isbn978-1-4799-2902-3-
dc.identifier.urihttp://hdl.handle.net/10722/191603-
dc.descriptionSession 1: Web Intelligence Foundations I-
dc.description.abstractStudying the propagation of social influence is critical in the analysis of online social networks. While most existing work focuses on the expected number of users influenced, the detailed probability distribution of users influenced is also significant. However, determining the probability distribution of the final influence propagation state is difficult. Monte-Carlo simulations may be used, but are computationally expensive. In this paper, we develop an analytical model for the influence propagation process in online social networks based on discretetime Markov chains, and deduce a closed-form equation for the n-step transition probability matrix. We show that given any initial state, the probability distribution of the final influence propagation state may be easily obtained from a matrix product. This provides a powerful tool to further understand social influence propagation.-
dc.languageengen_US
dc.publisherIEEE Computer Society. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001411-
dc.relation.ispartofIEEE/WIC/ACM International Conference on Web Intelligence (WI) Proceedingsen_US
dc.rightsIEEE/WIC/ACM International Conference on Web Intelligence (WI). Copyright © IEEE Computer Society.-
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.subjectSocial Network Intelligence-
dc.subjectSocial Influence Propagation-
dc.subjectAnalytical Model-
dc.subjectMarkov Chain-
dc.titleAn analytical model for the propagation of social influenceen_US
dc.typeConference_Paperen_US
dc.identifier.emailLi, VOK: vli@eee.hku.hken_US
dc.identifier.authorityLi, VOK=rp00150en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/WI-IAT.2013.2-
dc.identifier.hkuros225443en_US
dc.identifier.spage1-
dc.identifier.epage8-
dc.identifier.isiWOS:000331265000001-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 140218-

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