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research-article

Data-driven Sizing Specification Utilizing Consumer Text Reviews

[+] Author and Article Information
Rushtin Chaklader

OPEN Design Lab, Penn State University, University Park, PA 16802, U.S.A.
rxc341@gmail.com

Matthew B Parkinson

Professor, Engineering Design and Mechanical Engineering, Penn State University, University Park, PA 16802, U.S.A.
parkinson@psu.edu

1Corresponding author.

ASME doi:10.1115/1.4037476 History: Received February 20, 2017; Revised July 14, 2017

Abstract

The objective of this work is to introduce a new method for determining the design specifications related to human- artifact interaction. This new method uses data mining of large numbers of consumer reviews. User opinion on spe- cific product features can be time-consuming or expensive to obtain through traditional methods including surveys, ex- periments, and observational studies. Data mining review text of already released products may be a potentially less time consuming and costly method. Previously established methods of determining design for human variability infor- mation from consumer reviews, such as the Frequency and Accuracy Summation number and subsequent manual analy- sis, are explored. The Weighted Phrase Rating, a new metric which can be an automated tool to quickly analyze consumer reviews, is also introduced. It does not require manual pars- ing of the reviews, which extends its applicability to larger review pools. This new method is shown to quickly and eco- nomically provide information useful to the establishment of design specifications.

Copyright (c) 2017 by ASME
Topics: Design , Data mining
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