Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
The role of transparency in recommender systems
CHI '02 Extended Abstracts on Human Factors in Computing Systems
Is seeing believing?: how recommender system interfaces affect users' opinions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recommender Systems Research: A Connection-Centric Survey
Journal of Intelligent Information Systems
Trust building with explanation interfaces
Proceedings of the 11th international conference on Intelligent user interfaces
Inferring binary trust relationships in Web-based social networks
ACM Transactions on Internet Technology (TOIT)
Tagsplanations: explaining recommendations using tags
Proceedings of the 14th international conference on Intelligent user interfaces
Predicting tie strength with social media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A Survey of Explanations in Recommender Systems
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
On social networks and collaborative recommendation
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Personalized recommendation of social software items based on social relations
Proceedings of the third ACM conference on Recommender systems
A survey of collaborative filtering techniques
Advances in Artificial Intelligence
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
Providing Justifications in Recommender Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Multiple objective optimization in recommender systems
Proceedings of the sixth ACM conference on Recommender systems
Hidden factors and hidden topics: understanding rating dimensions with review text
Proceedings of the 7th ACM conference on Recommender systems
| Hi-index | 0.00 |
Recommender systems associated with social networks often use social explanations (e.g. "X, Y and 2 friends like this") to support the recommendations. We present a study of the effects of these social explanations in a music recommendation context. We start with an experiment with 237 users, in which we show explanations with varying levels of social information and analyze their effect on users' decisions. We distinguish between two key decisions: the likelihood of checking out the recommended artist, and the actual rating of the artist based on listening to several songs. We find that while the explanations do have some influence on the likelihood, there is little correlation between the likelihood and actual (listening) rating for the same artist. Based on these insights, we present a generative probabilistic model that explains the interplay between explanations and background information on music preferences, and how that leads to a final likelihood rating for an artist. Acknowledging the impact of explanations, we discuss a general recommendation framework that models external informational elements in the recommendation interface, in addition to inherent preferences of users.