Why CSCW applications fail: problems in the design and evaluationof organizational interfaces
CSCW '88 Proceedings of the 1988 ACM conference on Computer-supported cooperative work
Communications of the ACM
Reducing buyer search costs: implications for electronic marketplaces
Management Science - Special issue: Frontier research on information systems and economics
User Modeling and User-Adapted Interaction
Information Systems Research
Learning and reasoning about interruption
Proceedings of the 5th international conference on Multimodal interfaces
Experimental games for the design of reputation management systems
IBM Systems Journal
Interfaces for eliciting new user preferences in recommender systems
UM'03 Proceedings of the 9th international conference on User modeling
SuggestBot: using intelligent task routing to help people find work in wikipedia
Proceedings of the 12th international conference on Intelligent user interfaces
Encouraging Contributions to Online Communities with Personalization and Incentives
UM '07 Proceedings of the 11th international conference on User Modeling
Learning preferences of new users in recommender systems: an information theoretic approach
ACM SIGKDD Explorations Newsletter
The wisdom of the few: a collaborative filtering approach based on expert opinions from the web
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Rate it again: increasing recommendation accuracy by user re-rating
Proceedings of the third ACM conference on Recommender systems
Collaborative filtering recommender systems
The adaptive web
Social comparisons to motivate contributions to an online community
PERSUASIVE'07 Proceedings of the 2nd international conference on Persuasive technology
Social information access: the other side of the social web
SOFSEM'08 Proceedings of the 34th conference on Current trends in theory and practice of computer science
Encouraging user participation in a course recommender system: An impact on user behavior
Computers in Human Behavior
Proceedings of the fifth ACM conference on Recommender systems
Preference-based user rate correction process for interactive recommendation systems
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Social navigation support in a course recommendation system
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Collaborative Filtering Recommender Systems
Foundations and Trends in Human-Computer Interaction
Recommender systems: from algorithms to user experience
User Modeling and User-Adapted Interaction
The design space of opinion measurement interfaces: exploring recall support for rating and ranking
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Explaining the user experience of recommender systems
User Modeling and User-Adapted Interaction
Proceedings of the sixth ACM conference on Recommender systems
Preference-based user rating correction process for interactive recommendation systems
Multimedia Tools and Applications
Rating support interfaces to improve user experience and recommender accuracy
Proceedings of the 7th ACM conference on Recommender systems
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Economic modeling provides a formal mechanism to understand user incentives and behavior in online systems. In this paper we describe the process of building a parameterized economic model of user-contributed ratings in an online movie recommender system. We constructed a theoretical model to formalize our initial understanding of the system, and collected survey and behavioral data to calibrate an empirical model. This model explains 34% of the variation in user rating behavior. We found that while economic modeling in this domain requires an initial understanding of user behavior and access to an uncommonly broad set of user survey and behavioral data, it returns significant formal understanding of the activity being modeled.