Empirical Analysis of the User Reputation in User′s Object Bipartite Networks

LIU Xiaolu; JIA Shuwei; LIU Xiaolu; JIA Shuwei

doi:10.13306/j.1672-3813.2020.01.005

Complex Systems and Complexity Science >

2020 , Vol. 17 >Issue 1: 37 - 44

DOI: https://doi.org/10.13306/j.1672-3813.2020.01.005

Empirical Analysis of the User Reputation in User′s Object Bipartite Networks

LIU Xiaolu ,
JIA Shuwei ,
LIU Xiaolu ,
JIA Shuwei

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1.School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China;
2.College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China

Received date: 2019-09-25

Online published: 2020-04-29

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Abstract

User reputation measures user′s ability of rating accurate assessments of various objects,and is of great significance for ensuring the healthy development of social economy and people's livelihood.This paper empirically analyzed the user′s reputationin the MovieLens data setfrom two aspects of user′s activity and rating memory. Grouping by the user′s degree, the results showed that the user′s reputation increases with the user′s degree. When the data set was divided into 36 quarters according to the time, it was also found that the user′s reputation presents rising trend with the increase of the user′s degree. Moreover, the data set was divided into 9 years according to time, the results showed that the user's persistence rate is gradually reduced year by year. Furthermore, it presented a metric to measure the memory of user reputation. The results showed that the Kendall coefficients of user′s reputation ranking in 5 years are higher than those of user′s degree, indicating that the user′s reputation presents more memory than user′s activity. In addition, it proposed a null model to be compared with the empirical results. The results showed that the relationship between user′s reputation and degree as well as the memory of user reputation on the empirical data are significantly different from those of the null model.

Key words： user-object bipartite networks; user′s reputation; collective behavior analysis; memoryof user′s reputation

Cite this article

LIU Xiaolu , JIA Shuwei , LIU Xiaolu , JIA Shuwei . Empirical Analysis of the User Reputation in User′s Object Bipartite Networks[J]. Complex Systems and Complexity Science, 2020 , 17(1) : 37 -44 . DOI: 10.13306/j.1672-3813.2020.01.005

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