Premium
SmallWorlds: Visualizing Social Recommendations
Author(s) -
Gretarsson Brynjar,
O'Donovan John,
Bostandjiev Svetlin,
Hall Christopher,
Höllerer Tobias
Publication year - 2010
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2009.01679.x
Subject(s) - computer science , human–computer interaction , visualization , preference , variety (cybernetics) , recommender system , graph , information retrieval , information visualization , interface (matter) , user interface , world wide web , data mining , artificial intelligence , theoretical computer science , bubble , maximum bubble pressure method , parallel computing , economics , microeconomics , operating system
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.