Abstract
Existing research showed that voting the helpfulness of online reviews may not be the most appropriate measure of the quality of the information provided by those reviews. This paper suggests a new approach to rank online consumer reviews based on three variables of the relative information content of the textual portion of each review and the readability of that text, as reflecting how well the information is conveyed. The study shows the value of this approach over and above previous measures based on human votes. The study then extends that approach to the evaluation of the contribution of individual reviewers. The methodology was tested on 49,143 online reviews from three dissimilar product categories available on Amazon.com: appliances, computers, and luxury beauty. The implications of the proposed methodology and its potential applicability are discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 312-334 |
| Number of pages | 23 |
| Journal | Journal of Electronic Commerce Research |
| Volume | 27 |
| Issue number | 4 |
| State | Published - Nov 2026 |
Keywords
- e-Commerce
- e-WOM
- Information entropy
- Natural language processing
- Online consumer reviews
- Review helpfulness
- Reviewer expertise
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