Export bibliographic data
Literature by the same author
plus on the publication server
plus at Google Scholar


A Method and Analysis to Elicit User-Reported Problems in Intelligent Everyday Applications

Title data

Eiband, Malin ; Völkel, Sarah Theres ; Buschek, Daniel ; Cook, Sophia ; Hussmann, Heinrich:
A Method and Analysis to Elicit User-Reported Problems in Intelligent Everyday Applications.
In: ACM Transactions on Interactive Intelligent Systems. Vol. 10 (November 2020) Issue 4 .
ISSN 2160-6455
DOI: https://doi.org/10.1145/3370927

Project information

Project title:
Project's official titleProject's id
AI Tools - Continuous Interaction with Computational Intelligence ToolsNo information

Abstract in another language

The complex nature of intelligent systems motivates work on supporting users during interaction, for example, through explanations. However, as of yet, there is little empirical evidence in regard to specific problems users face when applying such systems in everyday situations. This article contributes a novel method and analysis to investigate such problems as reported by users: We analysed 45,448 reviews of four apps on the Google Play Store (Facebook, Netflix, Google Maps, and Google Assistant) with sentiment analysis and topic modelling to reveal problems during interaction that can be attributed to the apps’ algorithmic decision-making. We enriched this data with users’ coping and support strategies through a follow-up online survey (N = 286). In particular, we found problems and strategies related to content, algorithm, user choice, and feedback. We discuss corresponding implications for designing user support, highlighting the importance of user control and explanations of output rather than processes.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 02 Dec 2020 13:15
Last Modified: 02 Dec 2020 13:15
URI: https://eref.uni-bayreuth.de/id/eprint/59301