Decoding User Experience: A Study of Public EV Charging Stations Based on Amap Comments

<div class="section abstract"><div class="htmlview paragraph">The rapid expansion of the electric vehicle (EV) market has intensified the need for robust charging infrastructure. The quality of their experiences at public charging stations has become crucial to sustaining this transition. Key factors such as station accessibility, charging speed, and pricing transparency significantly affect user satisfaction. In Guangzhou, a China's major metropolitan city with an EV penetration rate exceeding 50%, this city offers an ideal context to assess the alignment between expanding EV infrastructure and user needs. This study examines user satisfaction with EV public charging stations in Guangzhou using a dataset of over 2,000 user comments from Amap. The comments are first processed using the Jieba segmentation library, with sentiment analysis conducted through the Natural Language Processing tool SnowNLP, categorizing comments by sentiment (419 positive, 156 neutral, and 1,690 negative). Term Frequency-Inverse Document Frequency(TF-IDF) is then applied for feature extraction, and the optimal number of clusters for K-means clustering was determined using the Elbow method. Findings reveal significant dissatisfaction with station availability, with 65.1% of negative comments highlighting insufficient charging spots even in high-charging-station-density districts. These results emphasize the need for improved resource allocation and introducing the "Pile Turnover Rate" (PTR) to enhance charging efficiency. Moreover, 21.01% of negative comments cite slow charging speeds and high costs, while fast-charging technology is praised in 47.97% of positive comments for its affordability and convenience. Variability in service pricing also contributes to dissatisfaction, with higher service price ratios strongly correlating with negative feedback. These findings provide actionable insights for policymakers and charging station operators to optimize EV infrastructure.</div></div>