|Title:||Mining perceptual maps from consumer reviews||Authors:||Lee A.J.T.
|Keywords:||Latent Dirichlet allocation;Opinion mining;Perceptual map;Radar chart;Sentiment analysis||Issue Date:||2016||Journal Volume:||82||Start page/Pages:||12-25||Source:||Decision Support Systems||Abstract:||
Consumer reviews are valuable resources for companies since consumers usually share their using experiences on products or provide useful opinions from various aspects such as different product features. Therefore, in this paper, we propose a method called MPM (mining perceptual map) to automatically build perceptual maps and radar charts from consumer reviews. Perceptual maps and radar charts are business tools widely used in marketing and business analysis. The proposed method may reduce subjective personal bias since perceptual maps and radar charts are mined from a large number of consumer reviews. The analysis results obtained from consumer reviews of smartphones show that the proposed method may provide some practical insights for smartphone companies. Our method can help companies position new products, and formulate effective marketing and competitive strategies. ? 2015 Elsevier B.V. All rights reserved.
Commerce; Data mining; Marketing; Radar; Smartphones; Statistics; Latent Dirichlet allocation; Opinion mining; Perceptual map; Radar chart; Sentiment analysis; Consumer behavior
|Appears in Collections:||資訊管理學系|
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