Peekaboom: a game for locating objects in images
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Designing games with a purpose
Communications of the ACM - Designing games with a purpose
Input-agreement: a new mechanism for collecting data using human computation games
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Matchin: eliciting user preferences with an online game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Mixing it up: recommending collections of items
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Guess who?: enriching the social graph through a crowdsourcing game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Perceptions, quality and motivational needs in image tagging human computation games
Journal of Information Science
Collaborative Filtering Recommender Systems
Foundations and Trends in Human-Computer Interaction
Games, Social Simulations, and Data-Integration for Policy Decisions: The SUDAN Game
Simulation and Gaming
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Collection recommender systems suggest groups of items that work well as a whole. The interaction effects between items is an important consideration, but the vast space of possible collections makes it difficult to analyze. In this paper, we present a class of games with a purpose for building collections where users create collections and, using an output agreement model, they are awarded points based on the collections that match. The data from these games will help researchers develop guidelines for collection recommender systems among other applications. We conducted a pilot study of the game prototype which indicated that it was fun and challenging for users, and that the data obtained had the characteristics necessary to gain insights into the interaction effects among items. We present the game and these results followed by a discussion of the next steps necessary to bring games to bear on the problem of creating harmonious groups.