Social media sentiment of hydrogen fuel cell vehicles in China: Evidence from artificial intelligence algorithms

Abstract

Hydrogen energy is significant in the energy consumption, especially in Hydrogen Fuel Cell Vehicles(HFCVs) market. Social media data is critical for exploring public perceptions of HFCVs. To find hot topics and understand the public sentiment of HFCVs, we employ a computational model, which combines Kmeans algorithm, Latent Dirichlet Allocation (LDA), and SnowNLP. The training data consists of 42,063 comments sourced from Bilibili-a popular Chinese social media platform. The analysis has identified 12 clusters, each with distinct topics and sentiments. The results reveal that the Chinese public generally holds a neutral stance on the hydrogen energy market, while some stakeholders maintain a positive on the technology and development of HFCVs, but some concerns about the transportation and safety of hydrogen fuel. Furthermore, this study offers suggestions for the technological, operational, and strategic advancement of HFCVs.