The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Designing novel review ranking systems: predicting the usefulness and impact of reviews
Abstract
With the rapid growth of the Internet, users' ability to publish content has created active electronic communities that provide a wealth of product information. Consumers naturally gravitate to reading reviews in order to decide whether to buy a product. However, the high volume of reviews that are typically published for a single product makes it harder for individuals to locate the best reviews and understand the true underlying quality of a product based on the reviews. Similarly, the manufacturer of a product needs to identify the reviews that influence the customer base, and examine the content of these reviews. In this paper, we propose two ranking mechanisms for ranking product reviews: a consumer-oriented ranking mechanism ranks the reviews according to their expected helpfulness, and a manufacturer-oriented ranking mechanism ranks the reviews according to their expected effect on sales. Our ranking mechanism combines econometric analysis with text mining techniques in general, and with subjectivity analysis in particular. We show that subjectivity analysis can give useful clues about the helpfulness of a review and about its impact on sales. Our results can have several implications for the market design of online opinion forums.
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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
Zhang, Z., Ye, Q., Law, R., & Li, Y. (2010) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2010.02.002 · Cited by 760
Chakraborty, I., Kim, M., & Sudhir, K. (2022) · Journal of Marketing Research · doi:10.1177/00222437211052500 · Cited by 84
Identifying helpful reviews based on customer’s mentions about experiences
Min, H.-J., & Park, J. C. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.01.116 · Cited by 66
Metadata
- Authors
- Ghose, A., & Ipeirotis, P. G.
- Venue
- Proceedings of the ninth international conference on Electronic commerce
- Publisher
- ACM
- Published
- 2007-08-19
- Pages
- 303-310
- OpenAlex
- W2099934438
- Cited by
- 322
- References
- 1
- FWCI
- 27.59
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Ghose, A., & Ipeirotis, P. G. (2007). Designing novel review ranking systems: predicting the usefulness and impact of reviews. Proceedings of the ninth international conference on Electronic commerce. https://doi.org/10.1145/1282100.1282158
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
