Public attention and sentiment towards clean heating in China: A text mining analysis based on Sina Weibo

Global warming and the increasing energy demand have heightened public interest in sustainable energy. However, few studies have effectively elucidated public attitudes and sentiments in the Chinese context, especially through analyses based on social media platforms. Therefore, this study used web crawlers to obtain 8743 posts and 3349 comments from Sina Weibo about clean heating (CH), integrating Latent Dirichlet Allocation topic modeling and SnowNLP sentiment analysis to explore the main topics of public concern and their sentiment divergence. The findings indicate that media units pay significant attention to CH. Public attention shows a fluctuating upward trend with regional differences. The economically developed eastern regions and energy-rich western regions are more concerned about CH. The five core topics discussed on Weibo and their percentages are the development trend of clean energy (24.6 %), sustainable development in rural areas (21.6 %), urban environmental protection and pollution control (21.2 %), rural heating issues (17.2 %), and application and challenges of energy-saving technologies (15.4 %). Sentiment analysis shows that residents’ positive sentiments towards CH are mainly driven by improving environmental quality. In contrast, negative sentiments stem from the high cost of heating and the “one-size-fits-all” problem in policy implementation. This study provides a theoretical basis for promoting sustainable energy technologies and policy formulation.