 Exploring the effect of dynamic seed activation in social networksSinjana Yerasani, Suprabhat Tripathi, Monalisa Sarma and Manoj Kumar Tiwari International Journal of Information Management, 2020, vol. 51, issue C Abstract: In this paper, we address the problem of maximizing the influence in a social network by hiring a few users in the network to propagate the information. Considering limited budget and time, hired users (seeds) are activated dynamically at different time intervals over a time horizon. This motivates to avoid the same seed activation in consecutive time intervals that leads to deteriorating the seeds’ efficiency. The aim of this paper is to maximize the total gain obtained in the process of maximizing the influence in a social network. Total gain is obtained by earning of influencing the customers and then deducting the cost incurred for influencing the users. Therefore, an improvised memetic algorithm is developed to find the seeds that are to be activated at different time intervals to maximize the gain. Experimental results validate the effectiveness of the proposed algorithm, and it is found to perform better in identifying the potential seeds with minimum expenditure. Keywords: Social networks; Influence maximization; Memetic algorithm; Local search (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:51:y:2020:i:c:s0268401219309855 DOI: 10.1016/j.ijinfomgt.2019.11.007 Access Statistics for this article International Journal of Information Management is currently edited by Yogesh K. Dwivedi More articles in International Journal of Information Management from Elsevier |
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