Finding the Least Significant Edges in the Active Subnets of a Social Network by Dragonfly Algorithm

Abstract
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The present study aimed at finding the least significant edges based on the target set selection. Selecting a target set consists of a subset of influential and effector nodes in an active social subnet to maximize the influence on the entire nodes of a network. The best heuristic algorithm only ensures that all nodes of a network can be influenced with a maximum of 63% of the target set selection. The concepts of vertex cover were used to find the active and influential nodes. The edges between the active or effector nodes were considered as significant edges while the other edges were considered as least significant. The experiment performed on four laboratory data and a real data showed that the proposed algorithm was more optimized.

Published In : IJCAT Journal Volume 6, Issue 1

Date of Publication : January 2019

Pages : 01-07

Figures :07

Tables :06

Publication Link :Finding the Least Significant Edges in the Active Subnets of a Social Network by Dragonfly Algorithm

Sadegh Saeedi : MSc student of computer engineering Department of Computer Engineering, Ahvaz Branch, Islamic Azad University, Iran.

Dr. Mohammad Hossein Yektaei : Ph.D. Assistant Professor, Department of Computer Engineering, Abadan Branch, Islamic Azad University, Iran.

Social network, least significant edges, Dragonfly Algorithm, target set selection

Today networks are widespread everywhere Spread of the networks in the world, It forces us to study them, Their study is based on the method of creating nodes and their relationship in the form of a model. The purpose of this article is to find least-significant edges.the least-significant edges will be obtained from significant-edges.

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