Deciphering the dynamics of risk perception: Emotional and cognitive responses to new energy vehicle crises on social media

Abstract

This study examines the impact of various stakeholders on the social amplification of risk perceptions regarding new energy vehicle technologies, focusing on Tesla-related discussions on Weibo. By applying natural language processing and machine learning to extract topics and conducting econometric analysis, we explored the emotional and cognitive dimensions of public discourse. Granger causality and impulse response analyses revealed that commercial media and celebrities initially intensified public negative emotions, while government communications mitigated them. Conversely, information from peer firms and the government positively influenced public risk perceptions on the cognitive dimension. Variance decomposition highlighted the rapid spread of emotionally driven content versus the deeper engagement elicited by cognitively driven content. These findings suggest that crisis communication strategies should consider the distinct dynamics of emotional and cognitive transmission on social media, providing valuable insights for managing public risk perceptions in crises.