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Bias-Aware Design for Informed Decisions: Raising Awareness of Self-Selection Bias in User Ratings and Reviews

Authors:

Xiaojuan MaAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 6, Issue CSCW2

Article No.: 496, Pages 1 - 31

https://doi.org/10.1145/3555597

Published: 11 November 2022 Publication History

Abstract

People often take user ratings/reviews into consideration when shopping for products or services online. However, such user-generated data contains self-selection bias that could affect people's decisions and it is hard to resolve this issue completely by algorithms. In this work, we propose to raise people's awareness of the self-selection bias by making three types of information concerning user ratings/reviews transparent. We distill these three pieces of information, i.e., reviewers' experience, the extremity of emotion, and reported aspect(s), from the definition of self-selection bias and exploration of related literature. We further conduct an online survey to assess people's perceptions of the usefulness of such information and identify the exact facets (e.g., negative emotion) people care about in their decision process. Then, we propose a visual design to make such details behind user reviews transparent and integrate the design into an experimental website for evaluation. The results of a between-subjects study demonstrate that our bias-aware design significantly increases people's awareness of bias and their satisfaction with decision-making. We further offer a series of design implications for improving information transparency and awareness of bias in user-generated content.

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Venugopal JSubramanian ASundaram GRivera MWheeler P(2024)A Comprehensive Approach to Bias Mitigation for Sentiment Analysis of Social Media DataApplied Sciences10.3390/app14231147114:23(11471)Online publication date: 9-Dec-2024
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Index Terms

Bias-Aware Design for Informed Decisions: Raising Awareness of Self-Selection Bias in User Ratings and Reviews
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

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Published In

cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 6, Issue CSCW2

CSCW

November 2022

8205 pages

EISSN:2573-0142

DOI:10.1145/3571154

Editor:
Jeff Nichols
Google

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Publication History

Published: 11 November 2022

Published in PACMHCI Volume 6, Issue CSCW2

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the Research Grants Council of the Hong Kong Special Administrative Region China under General Research Fund (GRF)

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Cited By

Šola HQureshi FKhawaja S(2024)AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case StudyBig Data and Cognitive Computing10.3390/bdcc81101448:11(144)Online publication date: 25-Oct-2024
https://doi.org/10.3390/bdcc8110144
Venugopal JSubramanian ASundaram GRivera MWheeler P(2024)A Comprehensive Approach to Bias Mitigation for Sentiment Analysis of Social Media DataApplied Sciences10.3390/app14231147114:23(11471)Online publication date: 9-Dec-2024
https://doi.org/10.3390/app142311471
Han SMikhailova D(2024)Reducing the Bias in Online Reviews Using Propensity Score AdjustmentCornell Hospitality Quarterly10.1177/1938965523122336465:4(429-441)Online publication date: 8-Jan-2024
https://doi.org/10.1177/19389655231223364
Zhu QWang DMa SWang AChen ZKhurana UMa X(2024)Towards Feature Engineering with Human and AI’s Knowledge: Understanding Data Science Practitioners’ Perceptions in Human&AI-Assisted Feature Engineering DesignProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661517(1789-1804)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661517
Ma SWang XLei YShi CYin MMa X(2024)“Are You Really Sure?” Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision MakingProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642671(1-20)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642671
Huth FBeck FKnittel JLatif SKoch SErtl T(2024)ViSCitR: Visual Summarization and Comparison of Hotel Reviews2024 IEEE 17th Pacific Visualization Conference (PacificVis)10.1109/PacificVis60374.2024.00021(112-121)Online publication date: 23-Apr-2024
https://doi.org/10.1109/PacificVis60374.2024.00021
Virvou M(2023)Artificial Intelligence and User Experience in reciprocity: Contributions and state of the artIntelligent Decision Technologies10.3233/IDT-23009217:1(73-125)Online publication date: 20-Apr-2023
https://doi.org/10.3233/IDT-230092
Kankham SHou J(2023)Right Sentiments to Spread the Word of Truth: Verified Ratings and Sentiment Polarity in Promoting Fact-Checking Contents on Social MediaSSRN Electronic Journal10.2139/ssrn.4595247Online publication date: 2023
https://doi.org/10.2139/ssrn.4595247

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