Detect Stable Community in Dynamic Social Networks Using Influential Nodes

Subject Areas : Electronics Engineering

Taleb khafaei ¹ , Alireza Tavakoli Taraghi ² , Mehdi Hoseyn Zadeh ³ , Ali Rezaee ⁴

1 - Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Computer Science Group of Mathematics Department, Shahid Beheshti University, Tehran, Iran
3 - Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran Computer Science, University of Human Development, Sulaymaniyeh, Irag
4 - Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Received: 2021-05-18 Accepted : 2021-12-14 Published : 2022-03-21

Keywords: important nodes, sustainable Community, Community, centrality Features, Social networks,

Abstract :

Social networks have found many applications in people's daily lives today so that identifying the behavior of members of these types of networks and associations within them is of particular importance. Due to the structure and the way of communication between the members of social networks, some members within this type of network have more important roles than other members. In this study, a method for identifying more important communities was discussed. For this purpose, new features were introduced using network centralization features and then the importance of this type of feature was investigated by Rough set theory. The experimental results showed that by increasing the number of popular nodes among a community where introduced in this study and at the same time decreasing the value of density, betweenness, and closeness centrality features of that community, it causes the effect of the number of popular nodes on the community will remain more evident.

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