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Content-oriented Evaluation and Detection for Product Reviews
Received date: 2014-05-04
Revised date: 2014-06-01
Online published: 2014-07-05
In order to access high-quality product reviews, this paper studied how to evaluate the quality of reviews and automatically identify the most useful reviews. It particularly examined how the textual aspect of a review affects the perceived usefulness, in terms of linguistic characteristics, semantics contents, and emotional tendencies. This paper adopted advanced text analysis techniques to extract feature indicators, validated their practicability through quantitative analysis and machine learning methods, and then designed a feasible utility-oriented prediction model. The results indicated that based on the review contents, reviews with high quality can be detected in order to improve the utility value of reviews.
Nie Hui . Content-oriented Evaluation and Detection for Product Reviews[J]. Library and Information Service, 2014 , 58(13) : 83 -89 . DOI: 10.13266/j.issn.0252-3116.2014.13.014
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