Application of data analytics for product design: Sentiment analysis of online product reviews. (November 2018)

• Record Type: Journal Article
• Authors: Ireland, Robert; Liu, Ang
• Is Part Of: CIRP journal of manufacturing science and technology. Volume 23(2018)
• Page Start: 128
• Page End: 144
• Publication Date: 2018-11
• Subjects: Design method -- Sentiment analysis -- Data analytics -- Online product review; Manufacturing processes -- Periodicals; 670.5
• DOI: 10.1016/j.cirpj.2018.06.003
• Languages: English
• ISSNs: 1755-5817

Abstract

Abstract: Advanced data analytics is one of the most revolutionary technological developments in the 21st century, which enables the discovery of underlining trends via sophisticated computational methods On various e-commerce and social platforms, millions of online product reviews are published by customers, which can potentially provide designers with invaluable insights into product design. This paper presents a design framework to analyze online product reviews. The objective is to use this machine-generated data to identify a series of customer needs. The framework aims to distill large volumes of qualitative data into quantitative insights on product features, so that designers can make more informed decisions. The framework combines the elements of online product reviews, design theory and methodology, and data analytics to reveal new insights. The effectiveness of the proposal framework is validated through a case study on product reviews from the e-commerce website, Amazon. The framework demonstrates a statistical approach for analyzing online product reviews. The framework acts as an interface between quantitative outputs and the qualitative and creative process of design. Further analysis of results identifies many of incorporating logical, computational methods into the highly subjective and creative process of design.