Consumer-generated online reviews of credence service providers, such as doctors, have become common on platforms such as Yelp and RateMDs. Yet doctors have challenged the legitimacy of these platforms on the grounds that consumers do not have the expertise required to evaluate the quality of the medical care they receive. This challenge is supported by the economics of information literature, which has characterized doctors as a credence service, meaning that consumers cannot evaluate quality even after consumption. Are interventions needed to ensure that consumers are not misled by these reviews? Data from real online reviews shows that many of the claims made in real reviews of credence service providers focus on experience attributes, such as promptness, which consumers can typically evaluate, rather than credence attributes, such as knowledge. Follow-up experiments show that consumers are more likely to believe experience claims (vs. credence claims) made by other consumers, claims that are supported by data, and longer reviews even if they are not more informative. The authors discuss implications for consumers and credence service providers and possible policy interventions.
This content will become publicly available on March 25, 2025
Not Just Algorithms: Strategically Addressing Consumer Impacts in Information Retrieval
Information Retrieval (IR) systems have a wide range of impacts on *consumers*.
We offer maps to help identify goals IR systems could---or should---strive for,
and guide the process of *scoping how to gauge a wide range of consumer-side
impacts and the possible interventions needed to address these effects. Grounded
in prior work on scoping algorithmic impact efforts, our goal is to promote and
facilitate research that (1) is grounded in impacts on information consumers,
contextualizing these impacts in the broader landscape of positive and negative
consumer experience; (2) takes a broad view of the possible means of changing or
improving that impact, including non-technical interventions; and (3) uses
operationalizations and strategies that are well-matched to the technical,
social, ethical, legal, and other dimensions of the specific problem in
question.
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- Award ID(s):
- 2415042
- PAR ID:
- 10497110
- Publisher / Repository:
- Springer
- Date Published:
- Journal Name:
- ECIR 2024: Advances in Information Retrieval
- Volume:
- 14611
- ISBN:
- 978-3-031-56066-8
- Page Range / eLocation ID:
- 314-335
- Subject(s) / Keyword(s):
- information access consumer-side impacts algorithmic harms
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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