SmallWorlds: Visualizing Social Recommendations |
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Authors: | Brynjar Gretarsson John O'Donovan Svetlin Bostandjiev Christopher Hall Tobias Höllerer |
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Affiliation: | Department of Computer Science, University of California, Santa Barbara |
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Abstract: | We present SmallWorlds, a visual interactive graph‐based interface that allows users to specify, refine and build item‐preference profiles in a variety of domains. The interface facilitates expressions of taste through simple graph interactions and these preferences are used to compute personalized, fully transparent item recommendations for a target user. Predictions are based on a collaborative analysis of preference data from a user's direct peer group on a social network. We find that in addition to receiving transparent and accurate item recommendations, users also learn a wealth of information about the preferences of their peers through interaction with our visualization. Such information is not easily discoverable in traditional text based interfaces. A detailed analysis of our design choices for visual layout, interaction and prediction techniques is presented. Our evaluations discuss results from a user study in which SmallWorlds was deployed as an interactive recommender system on Facebook. |
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Keywords: | H 3 3 [Information Interfaces and Presentation]: Information Storage and Retrieval— Information Search and Retrieval |
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