Today there are a huge quantity of online reviews available across different categories of products. The key question is how to select helpful online reviews and what can we learn from the abundant reviews. In this paper, we first conclude five categories of features to predict reviews' helpfulness from the perspective of a product designer and then present an approach based on conjoint analysis to measure customer requirement. The suggested approach are demonstrated using product data from a popular Chinese mobile phone market.
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Zhang et al. (2014) studied this question.
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