Structural Influence Maximization in Social Networks

Jing, Dong; Liu, Ting

doi:10.1109/ithings/greencom/cpscom/smartdata.2019.00186

Cited by 1 publication

(1 citation statement)

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“…The various studies show that information propagation to maximize the diffusion of influence in dynamic social networks. An algorithm and methods were developed to minimize the number of users or seeds with maximizing the influence and information diffusion in the social network within the given time bound [35][36][37][38][39][40]. Literature have also witnessed that researchers are looking towards the process of optimizing information propagation for various analyses.…”

Section: Related Workmentioning

confidence: 99%

Novel Approach for Optimizing Information Propagation in Dynamic Social Network

Selva

Kayavizhy

2020

Wseas Transactions on Computers

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Identification of potential node is one of the essential operations to be carried out in social network analysis as it is necessary to undertake various important decisions associated with the information propagation. Review of existing literature towards social network highlights that there is very less work carried out towards emphasizing potential node. Therefore, the proposed study offers a novel and unique solution that is capable of optimizing the level of information propagation when it is exposed to dynamic networks. The proposed study has been modeled using graph theory and it uses degree centrality distribution in order to offer more insight towards analyzing the selection of potential nodes in a social network. The study significantly contributes towards precise information propagation and its sustainability in the presence of dynamic social network in every aspect.

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