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DC FieldValueLanguage
dc.contributorDepartment of Computingen_US
dc.creatorLeung, Yee Hoi-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/7539-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titlePersuasion driven influence propagation in social networksen_US
dcterms.abstractWith the explosive growth of online social network services such as Facebook and Twitter, people now are providing ample opportunities to share information, ideas, and innovations among others. Studying social influence and information diffusion in online social networks can be extremely useful for various real-life applications, notably influencer marketing and viral marketing. Influence maximization problem, motivated by viral marketing applications, has received extensive attentions from social network analysis community in recent years. The goal of the problem is to find a small set of k seed nodes in a social network that maximize the influence spread under certain influence propagation models. Based on the widely adopted Independent Cascade model, a Persuasiveness Aware Cascade (PAC) model which considers social persuasion in influence propagation is proposed. In this model, the user-to-user influence probability is estimated by three types of social persuasion, namely, tie strength, peer conformity, and authority. Experiments conducted over real-world social networks suggest that he proposed model with the new social persuasion measures is more effective in describing real-world influence propagation than the well-studied propagation models for influence maximization.en_US
dcterms.extentix, 60 leaves : illustrations ; 30 cmen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2014en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHOnline social networks.en_US
dcterms.LCSHSocial media.en_US
dcterms.LCSHDigital communications -- Social aspects.en_US
dcterms.LCSHInternet -- Social aspects.en_US
dcterms.LCSHSocial influence.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/7539