Abstract
Identifying and analysing large amounts of online product reviews (OPR) have become a critical challenge for product design due to their valuable and insightful content. Despite the potential of the OPRs, designers cannot benefit from this opportunity because the analysis of the interpretations requires knowledge of different areas. This study proposes a novel framework for designers by utilizing online reviews for product design depending on the real-world OPRs of a sample product in terms of clarity, comparability, and validity. The framework contains five steps – retrieval of customer text, mining text polarity and product aspects by Document-Level Sentiment Analysis (DLSA) and Aspect-Based Sentiment Analysis (ABSA), summarizing and visualizing review candidate patterns by Correspondence Analysis (CA) and discovering and predicting possible causes of candidate patterns by correlation analysis.
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