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Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics

Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and... AbstractProviding explanations based on user reviews in recommender systems (RS) may increase users’ perception of transparency or effectiveness. However, little is known about how these explanations should be presented to users, or which types of user interface components should be included in explanations, in order to increase both their comprehensibility and acceptance. To investigate such matters, we conducted two experiments and evaluated the differences in users’ perception when providing information about their own profiles, in addition to a summarized view on the opinions of other customers about the recommended hotel. Additionally, we also aimed to test the effect of different display styles (bar chart and table) on the perception of review-based explanations for recommended hotels, as well as how useful users find different explanatory interface components. Our results suggest that the perception of an RS and its explanations given profile transparency and different presentation styles, may vary depending on individual differences on user characteristics, such as decision-making styles, social awareness, or visualization familiarity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png i-com de Gruyter

Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics

i-com , Volume 19 (3): 20 – Jan 26, 2021

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Publisher
de Gruyter
Copyright
© 2020 Walter de Gruyter GmbH, Berlin/Boston
ISSN
2196-6826
eISSN
2196-6826
DOI
10.1515/icom-2020-0021
Publisher site
See Article on Publisher Site

Abstract

AbstractProviding explanations based on user reviews in recommender systems (RS) may increase users’ perception of transparency or effectiveness. However, little is known about how these explanations should be presented to users, or which types of user interface components should be included in explanations, in order to increase both their comprehensibility and acceptance. To investigate such matters, we conducted two experiments and evaluated the differences in users’ perception when providing information about their own profiles, in addition to a summarized view on the opinions of other customers about the recommended hotel. Additionally, we also aimed to test the effect of different display styles (bar chart and table) on the perception of review-based explanations for recommended hotels, as well as how useful users find different explanatory interface components. Our results suggest that the perception of an RS and its explanations given profile transparency and different presentation styles, may vary depending on individual differences on user characteristics, such as decision-making styles, social awareness, or visualization familiarity.

Journal

i-comde Gruyter

Published: Jan 26, 2021

Keywords: Recommender systems; user study; explanations

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