# Sentiment Analysis of Online New Energy Vehicle Reviews
## 1 Introduction  
With increasing global environmental awareness and growing concerns about the scarcity of nonrenewable energy sources, the search for alternative clean energy solutions has become a significant issue across various industries [1]. As one of the primary modes of transportation, automobiles have raised concerns about emissions and resource consumption. To achieve the use of clean energy, the automotive industry needs a revolutionary change [2, 3]. In this context, electric vehicles (EVs) have emerged as an environmentally friendly and efficient alternative, demonstrating significant advantages. By delving into the technological innovations in the field of electric vehicles, a deeper understanding of their crucial benefits in reducing pollution, improving transportation, enhancing energy efficiency, and promoting sustainable development can be gained [4]. First, refs. [5, 6] focused on the application of electric vehicles in urban transportation and the potential for reducing traffic congestion, proposing a new perspective on improving urban traffic conditions. These studies, through methods such as traffic flow prediction and optimized operations, can improve traffic efficiency, reduce vehicle emissions, and improve urban air quality. Second, refs. [7, 8] delved into the underlying control and key technology applications of hybrid energy systems for electric vehicles. The aim of these studies was to enhance the performance and efficiency of electric vehicles, further promoting the utilization of renewable energy and energy transition. Additionally, refs. [9, 10] introduced the application of quantum algorithms and data augmentation techniques fortraffic predictions and translation tasks in electric vehicles. These novel approaches effectively enhance energy utilization efficiency and the quality of travel experience. On another front, refs. [8; 10] focused on the strategies for electric vehicles in the car-sharing market and the automatic parking system based on UWB (Ultra-Wideband) technology. These studies highlighted the potential of electric vehicles in the fields of shared mobility and intelligent transportation, driving urban sustainable development by providing convenient, economical, and environmentally friendly travel options. At the user level, refs. [11; 12] analyzed user emotions and experiences, revealing the evolution of electric vehicles in mixed learning environments and emotion detection in user interactions. These studies strengthened people's acceptance and recognition of electric vehicles, further driving their development and application. People's understanding and acceptance of electric vehicles will continue to improve. Before making a buying decision, consumers often rely on online reviews to understand how other customers evaluate EV performance, reliability, comfort, and other factors. However, sifting through a large volume of reviews can be challenging. This is where sentiment analysis comes into play, enabling consumers to quickly grasp the overall sentiment expressed by reviewers. By providing more comprehensive information and evaluations, sentiment analysis helps consumers gain a better understanding of the strengths and limitations of electric vehicles, facilitating more informed choices [3]. As a result, sentiment analysis plays a crucial role in the EV market, assisting consumers in making rational decisions and fostering the growth of the electric vehicle industry. User-generated content in the form of online reviews holds immense value and typically includes both ratings and textual descriptions [13]. While ratings are relatively straightforward to interpret, textual descriptions offer a wealth of nuanced information. For example, when it comes to vehicle comfort, some consumers might give a top rating of 5 stars, but their textual description may reveal negative experiences. Thus, sentiment analysis plays a vital role in discerning consumers' true opinions by leveraging natural language processing techniques [14].