| Current product design not merely takes the function and reliability into account,but also focus on the affective aspects to meet the consumers' affective needs.Conventionally,many previous studies obtain consumers' affective responses through questionnaire surveys,which is highly demanding on questionnaire design,small in scale,timeconsuming and labor-intensive,however.The lifecycle of a product is getting shorter and shorter and the social trends are changing continuously in a rapid economic development socity,resulting in the rapid change of consumers' affective responses accordingly.Therefore,it is necessary to develop an approach for collecting,identifying and analyzing consumers' affective responses effectively.Text mining is a computer processing technology that extracts valuable information from texts.Kansei Engineering is a user-oriented product development method that combines sensibility with engineering.This study proposes a sentiment minging method from online user reviews based on Kansei Engineering.It combines text mining and Kansei Engineering related methods and aims to collect,identify and analyze user's affective opinions toward products from online user reviews.This paper first proposes a sentiment minging method from online user reviews based on Kansei Engineering.Then,the proposed method is illustrated by an example.Finally,the affective topology of the product is established and a prototype system is developed to visualize the gap between user's affective responses and the affective design expectations of products,as well as the summary of the user's affective information towards products.In addition,an evaluation is also conducted for the proposed method using public data.The results show that the proposed method in this study can identify and extract the user's emotional information effectively.Besides,the gap between the user's affective responses and the affective design expectations can be identified and visualized effectively. |
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