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You Do Not Decide for Me! Evaluating Explainable Group Aggregation Strategies for Tourism

Authors:

Shabnam Najafian,

Nava TintarevAuthors Info & Claims

HT '20: Proceedings of the 31st ACM Conference on Hypertext and Social Media

Pages 187 - 196

https://doi.org/10.1145/3372923.3404800

Published: 13 July 2020 Publication History

Abstract

Most recommender systems propose items to individual users. However, in domains such as tourism, people often consume items in groups rather than individually. Different individual preferences in such a group can be difficult to resolve, and often compromises need to be made. Social choice strategies can be used to aggregate the preferences of individuals. We evaluated two explainable modified preference aggregation strategies in a between-subject study (n=200), and compared them with two baseline strategies for groups that are also explainable, in two scenarios: high divergence (group members with different travel preferences) and low divergence (group members with similar travel preferences). Generally, all investigated aggregation strategies performed well in terms of perceived individual and group satisfaction and perceived fairness. The results also indicate that participants were sensitive to a dictator-based strategy, which affected both their individual and group satisfaction negatively (compared to the other strategies).

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Cited By

Najafian SMusick GKnijnenburg BTintarev N(2023)How do people make decisions in disclosing personal information in tourism group recommendations in competitive versus cooperative conditions?User Modeling and User-Adapted Interaction10.1007/s11257-023-09375-w34:3(549-581)Online publication date: 12-Jul-2023
https://doi.org/10.1007/s11257-023-09375-w
Barile FDraws TInel ORieger ANajafian SEbrahimi Fard AHada RTintarev N(2023)Evaluating explainable social choice-based aggregation strategies for group recommendationUser Modeling and User-Adapted Interaction10.1007/s11257-023-09363-034:1(1-58)Online publication date: 21-Jun-2023
https://doi.org/10.1007/s11257-023-09363-0
Alvarado OHtun NJin YVerbert K(2022)A Systematic Review of Interaction Design Strategies for Group Recommendation SystemsProceedings of the ACM on Human-Computer Interaction10.1145/35551616:CSCW2(1-51)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555161

Index Terms

You Do Not Decide for Me! Evaluating Explainable Group Aggregation Strategies for Tourism
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. HCI design and evaluation methods
      1. Laboratory experiments
      2. User studies
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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cover image ACM Conferences

HT '20: Proceedings of the 31st ACM Conference on Hypertext and Social Media

July 2020

327 pages

ISBN:9781450370981

DOI:10.1145/3372923

General Chairs:
Anastasia Salter
University of Central Florida, USA
,
John F. Barber
Washington State University Vancouver, USA
,
Program Chair:
Ujwal Gadiraju
Delft University of Technology, The Netherlands

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 13 July 2020

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HT '20: 31st ACM Conference on Hypertext and Social Media

July 13 - 15, 2020

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Cited By

Najafian SMusick GKnijnenburg BTintarev N(2023)How do people make decisions in disclosing personal information in tourism group recommendations in competitive versus cooperative conditions?User Modeling and User-Adapted Interaction10.1007/s11257-023-09375-w34:3(549-581)Online publication date: 12-Jul-2023
https://doi.org/10.1007/s11257-023-09375-w
Barile FDraws TInel ORieger ANajafian SEbrahimi Fard AHada RTintarev N(2023)Evaluating explainable social choice-based aggregation strategies for group recommendationUser Modeling and User-Adapted Interaction10.1007/s11257-023-09363-034:1(1-58)Online publication date: 21-Jun-2023
https://doi.org/10.1007/s11257-023-09363-0
Alvarado OHtun NJin YVerbert K(2022)A Systematic Review of Interaction Design Strategies for Group Recommendation SystemsProceedings of the ACM on Human-Computer Interaction10.1145/35551616:CSCW2(1-51)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555161

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