The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Can online reviews reveal a product's true quality?: empirical findings and analytical modeling of Online word-of-mouth communication
Abstract
As a digital version of word-of-mouth, online review has become a major information source for consumers and has very important implications for a wide range of management activities. While some researchers focus their studies on the impact of online product review on sales, an important assumption remains unexamined, that is, can online product review reveal the true quality of the product? To test the validity of this key assumption, this paper first empirically tests the underlying distribution of online reviews with data from Amazon. The results show that 53% of the products have a bimodal and non-normal distribution. For these products, the average score does not necessarily reveal the product's true quality and may provide misleading recommendations. Then this paper derives an analytical model to explain when the mean can serve as a valid representation of a product's true quality, and discusses its implication on marketing practices.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Effect of Word of Mouth on Sales: Online Book Reviews
Chevalier, J. A., & Mayzlin, D. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.3.345 · Cited by 6,003
Cited by
Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
Luca, M., & Zervas, G. (2016) · Management Science · doi:10.1287/mnsc.2015.2304 · Cited by 1,263
Social Influence Bias: A Randomized Experiment
Muchnik, L., Aral, S., & Taylor, S. J. (2013) · Science · doi:10.1126/science.1240466 · Cited by 892
Do online reviews affect product sales? The role of reviewer characteristics and temporal effects
Hu, N., Liu, L., & Zhang, J. J. (2008) · Information Technology and Management · doi:10.1007/s10799-008-0041-2 · Cited by 659
Self-citationGhose, A., Ipeirotis, P. G., & Li, B. (2012) · Marketing Science · doi:10.1287/mksc.1110.0700 · Cited by 649
mTrust: discerning multi-faceted trust in a connected world
Tang, J., Gao, H., & Liu, H. (2012) · Proceedings of the fifth ACM international conference on Web search and data mining · doi:10.1145/2124295.2124309 · Cited by 337
Metadata
- Authors
- Hu, N., Pavlou, P. A., & Zhang, J.
- Venue
- Proceedings of the 7th ACM conference on Electronic commerce
- Publisher
- ACM
- Published
- 2006-06-11
- Pages
- 324-330
- OpenAlex
- W1993607151
- Cited by
- 379
- References
- 1
- FWCI
- 33.91
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Can online reviews reveal a product's true quality?: empirical findings and analytical modeling of Online word-of-mouth communication. https://app.cochat.ai/papers/10.1145/1134707.1134743
- The paper
- Hu, N., Pavlou, P. A., & Zhang, J. (2006). Can online reviews reveal a product's true quality?: empirical findings and analytical modeling of Online word-of-mouth communication. Proceedings of the 7th ACM conference on Electronic commerce. https://doi.org/10.1145/1134707.1134743
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
