Emotional contagion on social media and the simulation of intervention strategies after a disaster event: a modeling study

With the advent of climate change and the 5 G era, online communities are increasingly becoming the main medium for information dissemination after emergencies such as natural disasters. The widespread dissemination of negative online information may generate cyber violence or lead to serious adverse psychological outcomes. This study considered a natural disaster event involving avoidable deaths and child casualties as an example to identify emotional contagion and conduct simulation interventions. Data about the aftermath of the 8·13 flash flood in the Longcaogou Scenic Area, Sichuan Province, China, were derived from the Chinese Sina microblog. We analyzed key parameters and modeled them in a dynamic model. We further evaluated the effects of implementing intervention measures (such as transmission path interruption and changing the number of different emotions) on emotional spread. The overall sentiment of posters after this flood was negative, with three epidemic peaks. Negative emotions were more persistent and contagious than positive emotions. Reducing the number of negative blog posts by half could have led to a 14.97% reduction in negative comments and a 7.17% reduction in positive comments. Simultaneously, reducing the number of negative blog posts and increasing the number of positive posts would have helped reduce the relative ratio of negative to positive comments. The findings have theoretical and practical implications for developing an emotional contagion model and formulating intervention strategies to guide public opinion after an emergency that involves extensive online debate.