Cultural Creative Product Design Methods under the Path of User Empathy

Abstract

As consumption upgrades, China's cultural and creative industry is experiencing rapid growth. However, user empathy remains lacking in some products. This paper explores a design method for these products based on empathy theory. It employs the TF-IDF algorithm to extract semantic features from product texts and uses the SVM algorithm for classification. Post-classification, the LDA theme model analyzes sentiment, integrating both visual and semantic models to enhance product design. An analysis of cultural and creative products using data analysis software reveals that approximately 79.5% of user comments exhibit positive sentiment, with an average sentiment score of 2.9218 and a peak score of 39.1363. This suggests strong positive emotional responses from nearly 80% of users. The proposed method effectively enhances user-product interaction and empathy.