Title: Analysing the interrelationship between online reviews and sales: the role of review length and sentiment index in electronic markets

Authors: Anu G. Aggarwal; Aakash

Addresses: Department of Operational Research, University of Delhi, Delhi, India ' Department of Operational Research, University of Delhi, Delhi, India

Abstract: With the advent of electronic commerce, online customer reviews (OCRs) have become a significant source of information related to a product/service. Nowadays, lot of research is being carried out to understand the role played by OCRs on the buying intentions and product evaluation of the prospective customers. In this paper, we use log linear regression models to include the effects of product price, review length, review volume and sentiments (positive or negative words) on the sales of a product. Using Amazon.com review dataset, we show that in addition to the price, the customers are influenced by review volume, length, star rating and sentiment of reviews' text. We have also discussed the managerial as well as theoretical implication of the regression-based sales modelling integrated with information processing technique of text mining and sentiment analysis.

Keywords: electronic commerce; sentiment index; review length; text mining; sentiment analysis; online customer reviews; OCRs.

DOI: 10.1504/IJIMA.2020.111047

International Journal of Internet Marketing and Advertising, 2020 Vol.14 No.4, pp.361 - 376

Received: 22 Feb 2018
Accepted: 14 Mar 2019

Published online: 06 Nov 2020 *

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