Mining Social Discourse to Validate Behavioral Drivers: A Mixed-Methods Study on Rural Rooftop Photovoltaic Adoption in China

County-wide distributed rooftop photovoltaic (DRPV) systems, as an emerging form of renewable energy development, constitute a critical component for the low-carbon energy transition and carbon reduction. However, the pilot implementation in China has faced many challenges, with resistance from rural residents being a key issue requiring urgent resolution. This study aimed to investigate the underlying factors influencing their participation in DRPV and identify the key determinants. The topic modeling and evolutionary analysis were first conducted based on the multi-platform online textual data. The theoretical model was constructed combining the antecedent variables identified by the online textual analysis and the classic Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This model was validated through questionnaire surveys and structural equation modeling. The results revealed that facilitating conditions were the core determinant of rural residents’ participation in DRPV systems. Government-led safeguard mechanisms served as the primary enhancer of perceived convenience. Additionally, effort expectancy (0.301), performance expectancy (0.253), and social influence (0.424) all positively correlated with participation intention, with social influence exhibiting the strongest impact. Notably, rural residents equally prioritize environmental benefits and economic returns from DRPV systems. These findings provided policy insights for promoting DRPV projects in the future.