Expertise recommender: a flexible recommendation system and architecture
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
An algorithm for automated rating of reviewers
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Measuring user perceptions of web site reputation
Information Processing and Management: an International Journal
Third-Party Product Review and Firm Marketing Strategy
Marketing Science
Investigating interactions of trust and interest similarity
Decision Support Systems
A survey of trust and reputation systems for online service provision
Decision Support Systems
The roles of players and reputation: evidence from eBay online auctions
Decision Support Systems
Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites
Information Systems Research
Using Online Conversations to Study Word-of-Mouth Communication
Marketing Science
Designing novel review ranking systems: predicting the usefulness and impact of reviews
Proceedings of the ninth international conference on Electronic commerce
Effects of a reputation feedback system on an online consumer-to-consumer auction market
Decision Support Systems
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
Analysis of Web Trust Networks
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
Do online reviews affect product sales? The role of reviewer characteristics and temporal effects
Information Technology and Management
Do online reviews matter? - An empirical investigation of panel data
Decision Support Systems
Community gravity: measuring bidirectional effects by trust and rating on online social networks
Proceedings of the 18th international conference on World wide web
Voting Systems with Trust Mechanisms in Cyberspace: Vulnerabilities and Defenses
IEEE Transactions on Knowledge and Data Engineering
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Online opinion-sharing communities, which allow members to express personal opinions and preferences about specific products, provide important channels for consumers to learn about product quality and support their purchase decision process. Firms can use these reviews to understand customers' responses to their products and improve their products accordingly. Furthermore, opinion-sharing communities provide an alternative, effective marketing channel to firms by offering electronic word of mouth (eWOM). However, due to the openness and anonymity of opinion-sharing communities, their members face a challenging issue, that is, whether to believe or disbelieve information provided by other members. This study attempts to discriminate members (i.e., reviewers) with a high reputation from those with a low reputation on the basis of members' web trust network and review behaviors in an opinion-sharing community. We collected sample data pertaining to four product categories from Epinions.com to test our research model. The results indicate that four variables (trust intensity, average trust intensity of trustors, degree of review focus in the target category, and average product rating in the target category) successfully discriminate reviewers into the two groups, and product type is a significant control variable. These findings not only help firms identify reputable reviewers for marketing campaign purposes but also enable the members of an opinion-sharing community to determine who reputable reviewers are and whose reviews they should trust.