Hernandez-Bocanegra, Diana Carolina; Ziegler, Jürgen:
Explaining Review-Based Recommendations : Effects of Profile Transparency, Presentation Style and User Characteristics
In: i-com : Journal of Interactive Media, Vol. 19 (2021), No. 3, pp. 181 - 200
2021article/chapter in journalOA Bronze
Computer ScienceFaculty of Engineering » Computer Science and Applied Cognitive Science
Related: 2 publication(s)
Title in English:
Explaining Review-Based Recommendations : Effects of Profile Transparency, Presentation Style and User Characteristics
Author:
Hernandez-Bocanegra, Diana CarolinaUDE
GND
1256307963
LSF ID
60092
ORCID
0000-0002-1773-2633ORCID iD
SCOPUS
57218478446
Other
connected with university
Ziegler, JürgenUDE
GND
1015876811
GND
1077664516
LSF ID
3881
ORCID
0000-0001-9603-5272ORCID iD
SCOPUS
12797843900
SCOPUS
57205710998
SCOPUS
57208443887
SCOPUS
58059170700
Other
connected with university
Year of publication:
2021
Open Access?:
OA Bronze
Scopus ID
Language of text:
English
Keyword, Topic:
explanations ; Recommender systems ; user study

Abstract in English:

Providing 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.