Dynamic effects of emotions in microblogs on sharing during EID outbreaks: The contingent role of user personality traits

Our study empirically examines whether users’ personality traits accentuate or attenuate the influence of emotions in microblogs on users’ sharing behavior over time on a social media platform (Weibo in particular) during emerging infectious disease (EID) outbreaks. We develop a theoretical framework to analyze the dynamic relationship between emotions in microblogs related to EID on users’ sharing with personality traits as moderators. We collected 92,621 microblogs on COVID-19 from Sina Weibo with 501,930 sharing users for hypothesis testing. We leveraged a machine learning method in combination with the vector autoregression model to test our research model. Our results indicate that users with high levels of neuroticism, openness, and agreeableness are more likely to share immediately upon seeing microblogs with negative emotions, while those high in conscientiousness usually share after some time. This study highlights the contingent role of personality traits in the relationship between emotions expressed in microblogs and users’ act of sharing. The dynamic effects (both short-term and long-term) on sharing of emotions in microblogs are contingent upon personality traits. The results help us to understand who shares microblogs, how and why they behave when facing emotional content during EID outbreaks. Our findings enhance the understanding of user behavior on social media platforms and provide actionable insights for potential interventions in response to EID outbreaks.