Group Relationship Mining of College Students Based on Predictive Social Network

Author:

Liu Huazhang1ORCID

Affiliation:

1. Chongqing Industry Polytechnic College, Chonqing 401120, China

Abstract

With the rapid development of the Internet, social networks have shown an unprecedented development trend among college students. Closer social activities among college students have led to the emergence of college students with new social characteristics. The traditional method of college students’ group classification can no longer meet the current demand. Therefore, this paper proposes a social network link prediction method-combination algorithm, which combines neighbor information and a random block. By mining the social networks of college students’ group relationships, the classification of college students’ groups can be realized. Firstly, on the basis of complex network theory, the essential relationship of college student groups under a complex network is analyzed. Secondly, a new combination algorithm is proposed by using the simplest linear combination method to combine the proximity link prediction based on neighbor information and the likelihood analysis link prediction based on a random block. Finally, the proposed combination algorithm is verified by using the social data of college students’ networks. Experimental results show that, compared with the traditional link prediction algorithm, the proposed combination algorithm can effectively dig out the group characteristics of social networks and improve the accuracy of college students’ association classification.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Retracted: Group Relationship Mining of College Students Based on Predictive Social Network;Security and Communication Networks;2023-12-29

2. Research on the Application of Relationship Graphs in Data Analysis Algorithm Design;2023 IEEE 3rd International Conference on Electronic Technology, Communication and Information (ICETCI);2023-05-26

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