关键词: 大数据技术；汽车行业；用户评论；消费者满意度；自然语言处理

Abstract: With the development of the Chinese automobile industry and market, the automobile market has entered a stage of intense competition. It has become increasingly important to understand consumers' needs more accurately. In this study, a large amount of user review data on car purchases is collected using the internet, and big data technology is employed to analyze the data. Firstly, a significant amount of internet data is cleaned and classified. Then, through natural language processing techniques, sentiment analysis is conducted on all the review data for each car model, and a satisfaction index is constructed. Finally, through the analysis and visualization of the satisfaction index, the weights and thresholds of consumer satisfaction with different attributes of automotive products are determined. In addition to discovering general market patterns through numerical satisfaction index, this study further employ opinion extraction techniques to extract common positive or negative opinions of consumers towards specific attributes of automotive products from a large volume of review data. By utilizing satisfaction index and opinion extraction, this study, employs big data technology, obtains general patterns of consumer satisfaction with popular car models, provides clearer and more accurate guidance for the development of automotive products.

Key words: Big data technology; Automobile industry; Customer comments; Consumer satisfaction; Natural language processing