[Objective] This paper proposes a new method to explore consumer psychology and their preferences based on online comments, aiming to address the difficulties of drawing personality-based consumer portraits. [Methods] Firstly, we mapped relationship among the experience levels, product features and aspect words. Then, we extracted aspect words from user comments to examine their attentions at different experience levels. Third, we categorized users with their instinctual, behavioral, and reflective preferences. Finally, we utilized deep learning-based aspect sentiment analysis technology to examine user’s preferences for products. [Results] We evaluated our new model with more than 900 000 reviews on mobile phones from JD.com. Among them, users with instinctual preferences accounted for 41.60%, which was higher than behavioral preferences (33.01%) and reflective preferences (25.39%). We also analyzed their purchasing behaviors from the perspectives of brands and prices. [Limitations] We only collected review data on mobile phones sold by JD.com. More products and platforms need to be examined with our new model in the future. [Conclusions] The new model for creating user portraits can identify the preferences of different groups of consumers.
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