Nava, T., Rostami, S. and Smyth, B., 2018. Knowing the unknown: visualising consumption blind-spots in recommender system. In: SAC 2018 The 33rd ACM/SIGAPP Symposium On Applied Computing, 9-13 April 2018, Pau, France.
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Official URL: https://www.sigapp.org/sac/sac2018/
Abstract
In this paper we consider how to help users to better understand their consumption profiles by examining two approaches to visualising user profiles – chord diagrams, and bar charts – aimed at revealing to users those regions of the recommendation space that are unknown to them, i.e. blind-spots. Both visualisations do this by connecting profile preferences with a filtered recommendation space. We compare and contrast the two visualisations in a live user study (n = 70). The results suggest that, although users can understand both visualisations, chord diagrams are particularly effective in helping users to identify blind-spots, while simpler bar charts are better for conveying what was already known in a profile. Evaluating the understandability of blind-spot visualizations is a first step toward using visual explanations to help address a criticism of recommender systems: that personalising information creates filter bubbles.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Official website: The ACM Digital Library https://dl.acm.org/dl.cfm List of all the SAC conferences available from https://dl.acm.org/event.cfm?id=RE133 |
Uncontrolled Keywords: | Visualisation; Recommender Systems; Filter Bubble; Chord Diagram; |
Group: | Faculty of Science & Technology |
ID Code: | 30801 |
Deposited By: | Symplectic RT2 |
Deposited On: | 08 Jun 2018 15:09 |
Last Modified: | 14 Mar 2022 14:11 |
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