A Comparative Performance Evaluation of Search Items and Experience Items in Amazon Customer Reviews

Abstract

The accelerated growth of web users alongside developing the influence of online review web pages and social media has brought forth sentiment analysis assessment mining, which targets understanding what others think, assessments, comments and reviews about the item in social media, E-Commences sites, and so forth. The product review comments contributed by the customers have rich data about the use of the products. In this article, we have gathered reviews from Amazon.com by separating search items from experience items and we inspect the business effect of online reviews on product sales performance. This article looks at the impact of the degree of detail in an item review and the degree of analyst concurrence with it on the credibility of a review and customers' procurement expectations for search and experience items.