Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior
Proceedings of the 2nd ACM conference on Electronic commerce
Is seeing believing?: how recommender system interfaces affect users' opinions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
How opinions are received by online communities: a case study on amazon.com helpfulness votes
Proceedings of the 18th international conference on World wide web
Echoes of power: language effects and power differences in social interaction
Proceedings of the 21st international conference on World Wide Web
To switch or not to switch: understanding social influence in online choices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Incorporating reviewer and product information for review rating prediction
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Learning to identify review spam
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Controlling opinion bias in online social networks
Proceedings of the 3rd Annual ACM Web Science Conference
Controlling opinion propagation in online networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Opinions play an important role in trust building and the creation of consensus about issues and products and a number of studies have focused on the design, evaluation, and utilization of online opinion systems. However, little effort has been spent on the dynamic aspects of online opinion formation. In this article, we study the dynamics of online opinion expression by analyzing the temporal evolution of vey large sets of user views and determine that in the course of time, later opinions tend to show a big difference with earlier opinions, which moderates the average opinion to the less extreme. Online posters also tend to disagree with previous opinions when the cost of expression is high.