Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks  

作　　者：Farhan Amin Gyu Sang Choi 

机构地区：[1]Department of Information and Communication Engineering,Yeungnam University,Gyeongsan,38541,Korea

出　　处：《Computers, Materials & Continua》2022年第12期6367-6391,共25页计算机、材料和连续体（英文）

基　　金：This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education under Grant NRF-2019R1A2C1006159 and Grant NRF-2021R1A6A1A03039493;in part by the 2021 Yeungnam University Research Grant。

摘　　要：The Internet of Things(IoT)has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses.Social network analysis(SNA)is a good example that has recently gained a lot of scientific attention.It has its roots in social and economic research,as well as the evaluation of network science,such as graph theory.Scientists in this area have subverted predefined theories,offering revolutionary ones regarding interconnected networks,and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon.The motivation of this study is to understand and capture the clustering properties of large networks and social networks.We present a network growth model in this paper and build a scale-free artificial social network with controllable clustering coefficients.The random walk technique is paired with a triangle generating scheme in our proposed model.As a result,the clustering controlmechanism and preferential attachment(PA)have been realized.This research builds on the present random walk model.We took numerous measurements for validation,including degree behavior and the measure of clustering decay in terms of node degree,among other things.Finally,we conclude that our suggested random walk model is more efficient and accurate than previous state-of-the-art methods,and hence it could be a viable alternative for societal evolution.

关 键 词：Social networks small-world networks network generation models graph theory random walk network design social network analysis 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]