Sentiment mutation and negative emotion contagion dynamics in social media: A case study on the Chinese Sina Microblog

Negative emotional contagion along with sentiment mutation through information propagation on social media is critical for mitigating disinformation and directing public opinion for compliance with key public interventions, such as vaccine uptake during a pandemic. Here, we develop a dynamic multiple negative emotional susceptible-forwarding-immune (MNE-SFI) model to examine how negative emotion spreads on social media and how sentiment mutation impacts by fitting the model to real multiple temporal information in messages with sentiments obtained from the Chinese Sina microblog. Emotional choices, meaning that individuals attempting to spread information are not only influenced by the objective emotions embedded in the influential information spread by influencers but also by subjective emotional tendencies, is an essential human behavior for information propagation. Hence, we seek to link the negative emotional contagion in the network at the macroscopic level to the emotional choices of individuals, and model parameters are used at the microcosmic level to measure the “copying” and “mutation” probabilities of negative sentiments in an event. Our results illustrate the emotional choices of users play essential roles in methods for mitigating harmful emotion spread and promoting meaningful emotion diffusion.