SmallWorlds: Visualizing Social Recommendations

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 recommend...

• Type: Journal
• Year: 2010
• Where: CGF
• Authors: Brynjar Gretarsson, John O'Donovan, Svetlin Bostandjiev, Christopher Hall, Tobias Höllerer
• Keywords: CGF 2010, Interactive Graph-based Interface, Item Recommendations, Transparent Item Recommendations