A survey on influence maximization in a social network

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dc.contributor.author Banerjee, Suman
dc.contributor.author Jenamani, Mamata
dc.contributor.author Pratihar, Dilip Kumar
dc.date.accessioned 2020-04-27T05:22:47Z
dc.date.available 2020-04-27T05:22:47Z
dc.date.issued 2020-03
dc.identifier.citation Banerjee, Suman; Jenamani, Mamata and Pratihar, Dilip Kumar, "A survey on influence maximization in a social network", Knowledge and Information Systems, DOI: 10.1007/s10115-020-01461-4, Mar. 2020. en_US
dc.identifier.issn 0219-1377
dc.identifier.issn 0219-3116
dc.identifier.uri https://doi.org/10.1007/s10115-020-01461-4
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/5335
dc.description.abstract Given a social network with diffusion probabilities as edge weights and a positive integer k, which k nodes should be chosen for initial injection of information to maximize the influence in the network? This problem is popularly known as the Social Influence Maximization Problem (SIM Problem). This is an active area of research in computational social network analysis domain, since one and half decades or so. Due to its practical importance in various domains, such as viral marketing, target advertisement and personalized recommendation, the problem has been studied in different variants, and different solution methodologies have been proposed over the years. This paper presents a survey on the progress in and around SIM Problem. At last, it discusses current research trends and future research directions as well.
dc.description.statementofresponsibility by Suman Banerjee, Mamata Jenamani and Dilip Kumar Pratihar
dc.language.iso en_US en_US
dc.publisher Springer Verlag en_US
dc.title A survey on influence maximization in a social network en_US
dc.type Article en_US
dc.relation.journal Knowledge and Information Systems


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