Abstract
Online product reviews are an important type of user-generated content. For product designers, they offer valuable information that identifies consumer likes, dislikes and desires. We investigate the volume and quality of product design information available in online reviews and introduce the design-level information quality (DLIQ) measure. DLIQ is indicative of the design contextual information stored in the online reviews for a given product. Three separate information components are evaluated: content, complexity, and relevancy. Key determinants of DLIQ are the number of reviews, sentences, words, noun words and feature matching noun words in a review database. DLIQ is formulated as an index and indicates information content relative to a sample of products. For a sample of ten products, RapidMiner was used to mine and illustrate the DLIQ. A validation test with a survey group confirms DLIQ is a reliable predictor of actionable design information in the review database.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 102-110 |
| Number of pages | 9 |
| Journal | Electronic Commerce Research and Applications |
| Volume | 30 |
| DOIs | |
| State | Published - Jul 1 2018 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computer Networks and Communications
- Marketing
- Management of Technology and Innovation
Keywords
- Big data
- Data analytics
- Design features
- Information quality
- Online reviews
- Opinion mining
- Product design