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Improved Key Node Recognition Method of Social Network Based on PageRank Algorithm

Lei Hong1, Yiji Qian1,*, Chaofan Gong2, Yurui Zhang1, Xin Zhou3
1 Jiangsu Police Institute, Nanjing, 210000, China
2 Nanjing Police Station, Nanjing, 210000, China
3 System Consulting Pty Ltd., Sydney, 201101, Australia
* Corresponding Author: Yiji Qian. Email:

Computers, Materials & Continua 2023, 74(1), 1887-1903. https://doi.org/10.32604/cmc.2023.029180

Received 27 February 2022; Accepted 01 July 2022; Issue published 22 September 2022

Abstract

The types and functions of social networking sites are becoming more abundant with the prevalence of self-media culture, and the number of daily active users of social networking sites represented by Weibo and Zhihu continues to expand. There are key node users in social networks. Compared with ordinary users, their influence is greater, their radiation range is wider, and their information transmission capabilities are better. The key node users playimportant roles in public opinion monitoring and hot event prediction when evaluating the criticality of nodes in social networking sites. In order to solve the problems of incomplete evaluation factors, poor recognition rate and low accuracy of key nodes of social networking sites, this paper establishes a social networking site key node recognition algorithm (SNSKNIS) based on PageRank (PR) algorithm, and evaluates the importance of social networking site nodes in combination with the influence of nodes and the structure of nodes in social networks. This article takes the Sina Weibo platform as an example, uses the key node identification algorithm system of social networking sites to discover the key nodes in the social network, analyzes its importance in the social network, and displays it visually.

Keywords

Social networking site; PageRank algorithm; key node

Cite This Article

L. Hong, Y. Qian, C. Gong, Y. Zhang and X. Zhou, "Improved key node recognition method of social network based on pagerank algorithm," Computers, Materials & Continua, vol. 74, no.1, pp. 1887–1903, 2023.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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