Affect-inducing cues in risk messages: impact on collective negative emotions during public health emergencies

This study examines how "affect-inducing cues" in risk messages-fear appeals, outrage factors, risk stories, and visual elements-affect collective emotions during public health emergencies.

Using discussions about the COVID-19 variant "Xbb" on the Chinese Q&A platform Zhihu from December 2022 to January 2023, the study applies content analysis and fine-grained emotion analysis to measure these four cues, which serve as predictor variables. Additionally, a sentiment analysis method based on multiple sentiment lexicons and Chinese semantic rule sets is introduced to assess the prevalence of negative emotions among the message audience.

The findings reveal that the intensity of fear appeals in risk messages exhibits an inverted U-shaped relationship with the prevalence of negative emotions. Unexpectedly, risk stories reduce negative emotions, while the outrage factor and visual elements have no significant impact.

This study addresses the absence of a structural explanatory framework for collective emotional responses during public health emergencies, while practically providing new insights and empirical evidence for optimizing risk communication.