Using Text Mining of Amazon Reviews to Explore User-Defined Product Highlights and Issues

摘要

Advances in technology have made user-generated content ubiquitous. This includes user reviews of products which are publicly available on the internet and has led to an increase in the use of text mining to analyze consumer behavior. This paper presents a framework for using text mining to gather customer feedback. Text mining techniques are used to aggregate the top attributes associated with groups of devices, laptops and tablets, as well as individual devices. A case study comparison of three devices compares and contrasts positive and negative aspects mentioned by the users, which is useful to improve future generations of products. Manufacturers can incorporate and review product attributes when a product is launched and over time correct product issues, understand customer requirements, and maintain customer satisfaction.