A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes

The existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extrac...

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Main Authors: Yonghua Gong, Lei Chen, Tinghuai Ma
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Security and Communication Networks
Online Access:http://dx.doi.org/10.1155/2020/8887596
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spelling doaj-e37906c25dae4402ad89319daea5a3de2020-11-25T04:11:34ZengHindawi-WileySecurity and Communication Networks1939-01141939-01222020-01-01202010.1155/2020/88875968887596A Comprehensive Trust Model Based on Social Relationship and Transaction AttributesYonghua Gong0Lei Chen1Tinghuai Ma2School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaSchool of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaNanjing University of Information Science & Technology, Nanjing 210044, ChinaThe existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extracted from social links can improve the performance of trust and reputation mechanism, but the rates from these links in social commerce can be false because of the stakeholders’ manipulation for personal interest. And the rates are also dynamic and inconsistent. Therefore, this paper proposes a comprehensive trust model by fully exploiting the effects of the transaction attributes and social relationships on users’ trust. The proposed model refines the granularity of trust evaluation and improves the discrimination of recommended information. Experiments demonstrate that the proposed model performs better and predicts more accurately than the three models compared under the same circumstance.http://dx.doi.org/10.1155/2020/8887596
collection DOAJ
language English
format Article
sources DOAJ
author Yonghua Gong
Lei Chen
Tinghuai Ma
spellingShingle Yonghua Gong
Lei Chen
Tinghuai Ma
A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
Security and Communication Networks
author_facet Yonghua Gong
Lei Chen
Tinghuai Ma
author_sort Yonghua Gong
title A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
title_short A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
title_full A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
title_fullStr A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
title_full_unstemmed A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
title_sort comprehensive trust model based on social relationship and transaction attributes
publisher Hindawi-Wiley
series Security and Communication Networks
issn 1939-0114
1939-0122
publishDate 2020-01-01
description The existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extracted from social links can improve the performance of trust and reputation mechanism, but the rates from these links in social commerce can be false because of the stakeholders’ manipulation for personal interest. And the rates are also dynamic and inconsistent. Therefore, this paper proposes a comprehensive trust model by fully exploiting the effects of the transaction attributes and social relationships on users’ trust. The proposed model refines the granularity of trust evaluation and improves the discrimination of recommended information. Experiments demonstrate that the proposed model performs better and predicts more accurately than the three models compared under the same circumstance.
url http://dx.doi.org/10.1155/2020/8887596
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