User review helpfulness assessment based on sentiment analysis
ISSN: 0264-0473
Article publication date: 20 February 2020
Issue publication date: 13 May 2020
Abstract
Purpose
This paper aims to investigate the relationship between sentiment and review helpfulness and develop a method to fully use sentiment features in review helpfulness assessment. In addition, this paper explores whether product type influences evaluating review helpfulness.
Design/methodology/approach
First, a high-quality data set with a manually coded helpfulness score was constructed. Second, detailed research question methods were conducted. Finally, methods were applied to the data set to extract information gain and sentiment scores. Gradient boosting and random forest methods were used to classify the data set with these features through recall, precision and F-measure to understand the research questions.
Findings
Review sentiment has a deep relationship with review helpfulness, and it can be a strong predictor of review helpfulness by refining it into more detailed scores; a combination of sentiment scores and information gain works very well on classification for two product types. Product type does not show a significant influence on helpfulness assessment.
Originality/value
This paper provides a different perspective for measuring review sentiment by clarifying the relationship between sentiment and review helpfulness, analysing the role of product type in review helpfulness assessment, and proposing a high-value feature combination. In addition, the author believes that the assessment method can be effectively applied to practical works.
Keywords
Acknowledgements
This research was supported by: National Natural Science Foundation of China (Grant # 71673203); World First Class Subject Foundation of Ministry of Education of China [Library, Information and Data Science]; Key Research Institutes of Philosophy and Social Science by Ministry of Education, PR China (Grant # 16JJD870003); and the China Scholarship Council (Grant # 201806270049).
Citation
Zeng, Z., Zhou, Z. and Mu, X. (2020), "User review helpfulness assessment based on sentiment analysis", The Electronic Library, Vol. 38 No. 2, pp. 337-351. https://doi.org/10.1108/EL-08-2019-0200
Publisher
:Emerald Publishing Limited
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