文献类型：会议论文

英文题名：Event Graph Study of Typical Battery Electric Vehicle User Experience Based on Online Comments

作者：Gu, Quan[1];Zhang, Jie[1];Tan, Ruiguang[1];Cai, Yuchao[1];Wang, Chenlu[1]

机构：[1]East China Univ Sci & Technol, Sch Art Design & Media, Shanghai 200237, Peoples R China

会议论文集：26th International Conference on Human-Computer Interaction (HCII)

会议日期：JUN 29-JUL 04, 2024

会议地点：Washington, DC

语种：英文

外文关键词：Online comments; user experience; event graph; battery electric vehicle; natural language processing

摘要：Battery electric vehicles (BEVs) as representatives of environmentally friendly and future transportation have gained extensive attention. Research on user experience in the electric vehicle field has become increasingly important as it directly influences the market acceptance and sustainability of electric vehicles. This study aims to explore the user experience of typical battery electric vehicles and gain a deeper understanding of user perceptions, needs, and pain points using an event graph research method based on online comments. In the literature review, we examine the current state of battery electric vehicles and user experience research, identifying shortcomings in existing studies, particularly in dealing with challenges related to online comment data. Our approach involves data collection, data preprocessing, and event graph construction, utilizing natural language processing and data mining techniques to automatically extract user experience information from online comment data. By building an event graph of battery electric vehicle user experience, we can identify key events in different stages such as purchase, driving, maintenance, and charging, along with the emotions, satisfaction, and recommendations associated with these events. The results reveal that the user experience event graph not only aids in understanding users' overall perceptions of battery electric vehicles but also uncovers detailed user requirements, such as improvements in charging infrastructure, increased driving range, and vehicle performance enhancements. In the discussion section, we analyze the significance of the research findings and explore how battery electric vehicle manufacturers and government agencies can use this information to enhance products and policies. We also emphasize the limitations of this study, including data sources and event graph construction methods, and suggest future research directions, such as cross-cultural comparisons and user experience research for a broader range of vehicle types. In conclusion, the findings of this study provide valuable insights for the development of the battery electric vehicle industry and user satisfaction, offering useful guidance for future electric vehicle research and design.