Interpretable Perceived Topics in Online Customer Reviews for Product Satisfaction and Reader Helpfulness

Mirai Igarashi, Aijing Xing and Nobuhiko Terui

No 112, DSSR Discussion Papers from Graduate School of Economics and Management, Tohoku University

Abstract: Online customer reviews contain useful and important information, particularly, for product development and management, because customers praise or criticize in their reviews certain product attributes. We propose a model that extracts perceived topics from textual reviews using natural language processing under some restrictions created using seed words for improving the topic interpretability. In addition, the proposed model estimates the relationships between the topics and product satisfaction by writers of the review and the perceived helpfulness of reviews by readers, that is, these textual reviews are viewed as current product evaluations by customers who have made purchases and expectations of possible future demand by consumers who have yet to make purchases. The empirical study on e-commerce food reviews shows that our proposed model performs better than the extant alternative models and provides interesting findings such that the "ingredient" topic in the review text decreases the levels of customer satisfaction and the reader's perceived helpfulness. In contrast, the "health" topic increases the levels of both customer satisfaction and the reader's perceived helpfulness. These findings help us understand the product attributes that purchased customers are satisfied with and for which readers of reviews find helpful information.

Pages: 28 pages
Date: 2020-04
New Economics Papers: this item is included in nep-pay
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10097/00127714

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:toh:dssraa:112

Access Statistics for this paper

More papers in DSSR Discussion Papers from Graduate School of Economics and Management, Tohoku University Contact information at EDIRC.
Bibliographic data for series maintained by Tohoku University Library ().