Examining and Improving the Effectiveness of Trust Model for Online Reputation System

Author(s):  
Zhang Wei ◽  
Zhu Yanchun
2010 ◽  
Vol 121-122 ◽  
pp. 429-434
Author(s):  
Jun Mei Wang ◽  
Li Wang ◽  
Jun Xie

The mistrust between buyers and sellers in C2C electronic commerce has been affecting its development. The accuracy and the reliability of the reputation system are still not high because of the existence of vicious users. This paper builds a comprehensive reputation based trust model by choosing the suitable influential factors in trust and the simulation results prove that this model has a higher accuracy and reliability.


2019 ◽  
Vol 11 (17) ◽  
pp. 4802 ◽  
Author(s):  
Lirong Chen ◽  
Wenli Li ◽  
Hao Chen ◽  
Shidao Geng

Online reputation systems play an important role in reducing consumers’ purchase uncertainty in online shopping. However, some sellers manipulate reviews for their own interests, which reduces the effectiveness of the reputation system. Unlike the previous studies, which focus on features of reviews and reviewers, this study establishes a game model to analyze sellers’ manipulation behavior and identifies what kind of sellers or under what scenario sellers are motivated to manipulate reviews. Our study provides a new perspective for platform to detect fake reviews and helps consumers to make good use of online reviews without getting trapped in some sellers’ fraudulent manipulation.


Author(s):  
Li Xiong ◽  
Ling Liu

This chapter introduces reputation systems as a means of facilitating trust and minimizing risks in m-commerce and e-commerce in general. It first illustrates the importance of reputation systems in m-commerce by analyzing a list of risks through example scenarios and discusses a number of challenges of building an effective and robust reputation system in e-commerce applications. It then describes PeerTrust, an adaptive and dynamic reputation based trust model that helps participants or peers to evaluate the trustworthiness of each other based on the community feedback about participants’ past behavior. It also presents some initial experiments showing the effectiveness, benefit and vulnerabilities of the reputation systems. Finally it discusses a few interesting open issues.


2019 ◽  
Vol 16 (7) ◽  
pp. 174-194 ◽  
Author(s):  
Weijin Jiang ◽  
Yang Wang ◽  
Yirong Jiang ◽  
Jiahui Chen ◽  
Yuhui Xu ◽  
...  

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