Communications of the ACM
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Republic.com
Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
IEEE Transactions on Knowledge and Data Engineering
Recommender systems and their impact on sales diversity
Proceedings of the 8th ACM conference on Electronic commerce
When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry
Journal of Management Information Systems
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Serendipitous recommendations via innovators
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
An analysis of the importance of the long tail in search engine marketing
Electronic Commerce Research and Applications
The impact of YouTube recommendation system on video views
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Boosting video popularity through recommendation systems
Databases and Social Networks
Utilizing marginal net utility for recommendation in e-commerce
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Looking for "good" recommendations: a comparative evaluation of recommender systems
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part III
The effect of context-aware recommendations on customer purchasing behavior and trust
Proceedings of the fifth ACM conference on Recommender systems
Rank and relevance in novelty and diversity metrics for recommender systems
Proceedings of the fifth ACM conference on Recommender systems
Workshop on novelty and diversity in recommender systems - DiveRS 2011
Proceedings of the fifth ACM conference on Recommender systems
Technology Dominance in Complex Decision Making: The Case of Aided Credibility Assessment
Journal of Management Information Systems
Drivers of the Long Tail Phenomenon: An Empirical Analysis
Journal of Management Information Systems
The impact of recommender systems on item-, user-, and rating-diversity
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Recommender systems: from algorithms to user experience
User Modeling and User-Adapted Interaction
ACM Transactions on Interactive Intelligent Systems (TiiS)
Electronic Commerce Research and Applications
Proceedings of the 14th Annual International Conference on Electronic Commerce
Case study on the business value impact of personalized recommendations on a large online retailer
Proceedings of the sixth ACM conference on Recommender systems
Workshop on recommendation utility evaluation: beyond RMSE -- RUE 2012
Proceedings of the sixth ACM conference on Recommender systems
Measuring the coverage and redundancy of information search services on e-commerce platforms
Electronic Commerce Research and Applications
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Proceedings of the 28th Annual ACM Symposium on Applied Computing
A hidden Markov model for collaborative filtering
MIS Quarterly
Proceedings of the 7th ACM international conference on Web search and data mining
Who likes it more?: mining worth-recommending items from long tails by modeling relative preference
Proceedings of the 7th ACM international conference on Web search and data mining
Exploring the filter bubble: the effect of using recommender systems on content diversity
Proceedings of the 23rd international conference on World wide web
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This paper examines the effect of recommender systems on the diversity of sales. Two anecdotal views exist about such effects. Some believe recommenders help consumers discover new products and thus increase sales diversity. Others believe recommenders only reinforce the popularity of already-popular products. This paper seeks to reconcile these seemingly incompatible views. We explore the question in two ways. First, modeling recommender systems analytically allows us to explore their path-dependent effects. Second, turning to simulation, we increase the realism of our results by combining choice models with actual implementations of recommender systems. We arrive at three main results. First, some well-known recommenders can lead to a reduction in sales diversity. Because common recommenders (e.g., collaborative filters) recommend products based on sales and ratings, they cannot recommend products with limited historical data, even if they would be rated favorably. In turn, these recommenders can create a rich-get-richer effect for popular products and vice versa for unpopular ones. This bias toward popularity can prevent what may otherwise be better consumer-product matches. That diversity can decrease is surprising to consumers who express that recommendations have helped them discover new products. In line with this, result two shows that it is possible for individual-level diversity to increase but aggregate diversity to decrease. Recommenders can push each person to new products, but they often push users toward the same products. Third, we show how basic design choices affect the outcome, and thus managers can choose recommender designs that are more consistent with their sales goals and consumers' preferences.