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.
Original language | English |
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Title of host publication | SAC '18 |
Subtitle of host publication | Proceedings of the 33rd Annual ACM Symposium on Applied Computing |
Place of Publication | New York |
Publisher | Association for Computer Machinery |
Pages | 1396-1399 |
Number of pages | 4 |
ISBN (Print) | 978-1-4503-5191-1 |
DOIs | |
Publication status | Published - 2018 |
Event | SAC 2018: The 33rd ACM/SIGAPP Symposium On Applied Computing - Pau, France Duration: 9 Apr 2018 → 13 Apr 2018 Conference number: 33rd |
Conference
Conference | SAC 2018 |
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Abbreviated title | SAC'18 |
Country/Territory | France |
City | Pau |
Period | 9/04/18 → 13/04/18 |
Bibliographical note
Accepted author manuscriptKeywords
- Visualisation
- Recommender Systems
- Filter Bubble
- Chord Diagram