Presenting a Novel Method for Identifying Communities in Social Networks Based on the Clustering Coefficient

doi:10.14569/IJACSA.2023.0140887

CQUET-IR

	Presenting a Novel Method for Identifying Communities in Social Networks Based on the Clustering Coefficient
	He, Zhihong 1; Liu, Tao 2
	2023
发表期刊	International Journal of Advanced Computer Science and Applications
ISSN	2158-107X
EISSN	2156-5570
卷号	14 期号:8 页码:786-794
摘要	In recent decades, social networks have been considered as one of the most important topics in computer science and social science. Identifying different communities and groups in these networks is very important because this information can be useful in analyzing and predicting various behaviors and phenomena, including the spread of information and social influence. One of the most important challenges in social network analysis is identifying communities. A community is a collection of people or organizations that are more densely connected than other network entities. In this article, a method to increase the accuracy, quality, and speed of community detection using the Fire Butterfly algorithm is presented, which defines the algorithm and fully introduces the parameters used in the proposed algorithm and how to implement it. In this method, first the social network is converted into a graph and then the clustering coefficient is calculated for each node. Also, the butterfly algorithm based on the clustering coefficient (CC-BF) has been proposed to identify complex social networks. The proposed algorithm is new both in terms of generating the initial population and in terms of the mutation method, and these improve its efficiency and accuracy. This research is inspired by the meta-heuristic algorithm of Butterfly Flame based on the clustering coefficient to find active nodes in the social network. The results have shown that the proposed algorithm has improved by 23.6% compared to previous similar works. The findings of this research have great value and can be useful for researchers in computer science, social network managers, data analysts, organizations and companies, and other general public. © (2023), (Science and Information Organization). All Rights Reserved.
关键词	Behavioral research Clustering algorithms Social networking (online) Butterfly algorithms Butterfly fire algorithm Clustering coefficient Detection of community Network-based Novel methods Social influence Social network Social Network Analysis Spread of informations
DOI	10.14569/IJACSA.2023.0140887
收录类别	EI ; ESCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Theory & Methods
WOS记录号	WOS:001064721700001
出版者	Science and Information Organization
EI入藏号	20233814768323
原始文献类型	Journal article (JA)
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.cqcet.edu.cn/handle/39TD4454/18056
专题	重庆电子科技职业大学
作者单位	1.College of Art and Design, Chongqing Vocational College of Culture and Arts, Chongqing; 400067, China; 2.College of Artificial Intelligence and Big Data, Chongqing College of Electronic Engineering, Chongqing; 401331, China
推荐引用方式 GB/T 7714	He, Zhihong,Liu, Tao. Presenting a Novel Method for Identifying Communities in Social Networks Based on the Clustering Coefficient[J]. International Journal of Advanced Computer Science and Applications,2023,14(8):786-794.
APA	He, Zhihong,&Liu, Tao.(2023).Presenting a Novel Method for Identifying Communities in Social Networks Based on the Clustering Coefficient.International Journal of Advanced Computer Science and Applications,14(8),786-794.
MLA	He, Zhihong,et al."Presenting a Novel Method for Identifying Communities in Social Networks Based on the Clustering Coefficient".International Journal of Advanced Computer Science and Applications 14.8(2023):786-794.