The Effect of Online Reviews on E-book Pricing: A Text Analytics Approach

Abstract

In this paper, we explore how online reviews affect e-book prices via analyzing the sheer volume online data from the e-book websites. Namely, we first employ a domain ontology-based method to select the most discriminative features that may affect the e-book prices. Then, the topic modeling method latent Dirichlet allocation and aspect-oriented sentiment analysis method are applied as a supplement. Using the multiple regression method, we identify the key attributes that may influence the prices of e-books and give the related regression equation. The managerial implication is that firms can obtain a reference price for an e-book and may dynamically adjust the price to increase e-book sales according to our data analysis results.