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

Guy Laban, Theo Araujo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

34 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 20th ACM International Conference on Intelligent Virtual Agents, IVA 2020
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450375863
DOIs
StatePublished - 20 Oct 2020
Externally publishedYes
Event20th ACM International Conference on Intelligent Virtual Agents, IVA 2020 - Virtual, Online, United Kingdom
Duration: 20 Oct 202022 Oct 2020

Publication series

NameProceedings of the 20th ACM International Conference on Intelligent Virtual Agents, IVA 2020

Conference

Conference20th ACM International Conference on Intelligent Virtual Agents, IVA 2020
Country/TerritoryUnited Kingdom
CityVirtual, Online
Period20/10/2022/10/20

Keywords

  • Anthropomorphism
  • Chatbots
  • Conversational Agents
  • E-commerce
  • Personalization
  • Privacy
  • Recommender Systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction

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