Effects and Mechanism of Weibo’s Negative Emotions on Covid-19 Related Retweets Based on Big Data Collection Technology

ABSTRACT

This study based on big data collection technology with Weibo contents to reveal the relationship between negative emotion and information diffusion during Covid-19 pandemic. Specifically, focusing on how negative emotion influences the number of reposts (retweets). From January 23 to February 7 2020, 176,934 Weibo posts collected with the keyword “novel coronavirus pneumonia”. Negative binomial regression method is applied to construct an empirical model between negative emotion and retweets. Regression results demonstrated that there is not a single linear relationship between the two, when the negative emotion exceed a certain level, retweets would decrease instead. Our results implicate risk communication can be manipulated by controlling the negative intensity in social media contents, even under extreme risk. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.