Hernandez Bocanegra, Diana Carolina; Ziegler, Jürgen:
Effects of Interactivity and Presentation on Review-Based Explanations for Recommendations
In: Human-Computer Interaction – INTERACT 2021 : Proceedings, Part II / Ardito, Carmelo; Lanzilotti, Rosa; Malizia, Alessio; Petrie, Helen; Piccinno, Antonio; Desolda, Giuseppe; Inkpen, Kori (Eds.). - 18th IFIP TC 13 International Conference, Bari, Italy, August 30 – September 3, 2021 - Cham: Springer, 2021 - (Lecture Notes in Computer Science ; 12933) (Information Systems and Applications, incl. Internet/Web, and HCI ; 12933), pp. 597 - 618
2021book article/chapter in ProceedingsOA Green
Computer ScienceFaculty of Engineering » Computer Science and Applied Cognitive Science » Computer Science » Interactive Systems
Title in English:
Effects of Interactivity and Presentation on Review-Based Explanations for Recommendations
Author:
Hernandez Bocanegra, Diana CarolinaSCOPUSLSF; Ziegler, JürgenSCOPUSLSF
Open Access?:
OA Green
Scopus ID:
arXiv.org ID:
Language of text:
English
Keyword, Topic:
Explanations ; Interactivity ; Recommender systems ; User characteristics ; User study

Abstract in English:

User reviews have become an important source for recommending and explaining products or services. Particularly, providing explanations based on user reviews may improve users’ perception of a recommender system (RS). However, little is known about how review-based explanations can be effectively and efficiently presented to users of RS. We investigate the potential of interactive explanations in review-based RS in the domain of hotels, and propose an explanation scheme inspired by dialogue models and formal argument structures. Additionally, we also address the combined effect of interactivity and different presentation styles (i.e. using only text, a bar chart or a table), as well as the influence that different user characteristics might have on users’ perception of the system and its explanations. To such effect, we implemented a review-based RS using a matrix factorization explanatory method, and conducted a user study. Our results show that providing more interactive explanations in review-based RS has a significant positive influence on the perception of explanation quality, effectiveness and trust in the system by users, and that user characteristics such as rational decision-making style and social awareness also have a significant influence on this perception.