Based on Data-Driven Research on the Emotional Experience of Electric Vehicle Users

Abstract

Under the global goal of "dual carbon", rich and diversified new energy vehicle products continue to meet market demand, and new energy vehicles are increasingly recognized by consumers, but the current evaluation research on their user emotions is still insufficient. In order to more accurately understand the relatively real user emotional experience of electric vehicles, this paper proposes a method for collecting, drawing and analyzing these online reviews based on the online comment text of electric vehicle big data, text mining and natural language processing, and combined with the sentiment analysis method of user evaluation. Firstly, taking the typical electric car BYD-Song PLUS as an example, the online short text review about BYD-Song PLUS on the online review website is obtained through the crawler software; Secondly, natural language processing technology is used to preprocess the data to obtain the visual statistics of word frequency related to eight subject words. Then, a user sentiment analysis method is established to obtain sentiment analysis of short text data. Finally, combined with the theory of emotional experience, the application of emotional experience electric vehicles is analyzed from three aspects: instinctual level, behavioral level and reflection level. Compared with the traditional research focusing on individual user evaluation, this study explores the possibility of a user perceptual evaluation research method in the context of big data. This will provide a certain theoretical reference for the research of user perceptual evaluation system, and help people related to new energy vehicles and even more related products to understand the emotional experience of users closer to the truth.