The Effect of Personalization Techniques in Users' Perceptions of Conversational Recommender Systems

Open Access
Authors
Publication date 2020
Book title IVA '20: Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents
ISBN (electronic)
  • 9781450375863
Event 20th ACM International Conference on Intelligent Virtual Agents, IVA 2020
Article number 34
Number of pages 3
Publisher New York: Association for Computing Machinery
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Amsterdam School of Communication Research (ASCoR)
Abstract
Conversational recommender systems provide users with individually tailored recommendations in a flowing dialogue. These require users to disclose information proactively or reactively for receiving personalized recommendations, which can trigger users' resistance to the platform and to the recommendations. Accordingly, this study examined the extent to which user-initiated and system-initiated recommendations provided by a conversational recommender system influenced users' perceptions of it. The results of an online experiment entail that when recommendations are system-initiated, as compared to user-initiated, users perceive to be in less control and perceive the system as riskier. Furthermore, the results stress that systems that provide user-initiated or system-initiated recommendations do not differ in users' perceptions of anthropomorphism.
Document type Conference contribution
Language English
Published at https://doi.org/10.1145/3383652.3423890
Other links https://www.scopus.com/pages/publications/85096954637
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