Influence maximization in large social networks: Heuristics, models and parameters

dc.contributor.authorSumith, N.
dc.contributor.authorAnnappa, B.
dc.contributor.authorBhattacharya, S.
dc.date.accessioned2026-02-05T09:30:50Z
dc.date.issued2018
dc.description.abstractOnline social networks play a major role not only in socio psychological front, but also in the economic aspect. The way social network serves as a platform of information spread, has attracted a wide range of applications at its doorstep. In recent years, lot of efforts are directed to use the phenomenon of vast spread of information, via social networks, in various applications, ranging from poll analysis, product marketing, identifying influential users and so on. One such application that has gained research attention is the influence maximization problem. The influence maximization problem aims to fetch the top influential users in the social networks. The aim of the paper is to provide a comprehensive analysis on the state of art approaches towards identifying influential users. In this review, we discuss various challenges and approaches to identify influential users in online social networks. This review concludes with future research direction, helping researchers to bring possible improvements to the existing body of work. © 2018 Elsevier B.V.
dc.identifier.citationFuture Generation Computer Systems, 2018, 89, , pp. 777-790
dc.identifier.issn0167739X
dc.identifier.urihttps://doi.org/10.1016/j.future.2018.07.015
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/24910
dc.publisherElsevier B.V.
dc.subjectAlgorithms
dc.subjectCommerce
dc.subjectMarketing
dc.subjectModels
dc.subjectStructure (composition)
dc.subjectComprehensive analysis
dc.subjectFuture research directions
dc.subjectInfluence maximizations
dc.subjectInfluential users
dc.subjectOn-line social networks
dc.subjectProduct marketing
dc.subjectSpread of informations
dc.subjectViral marketing
dc.subjectSocial networking (online)
dc.titleInfluence maximization in large social networks: Heuristics, models and parameters

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