The evolution mechanism of social emotions during the Covid‑19 pandemic:an analysis based on big data from Twitter and GDELT  

作　　者：Gong Weigang Zhu Meng Chen Hao 

机构地区：[1]Department of Sociology,Wuhan University,Wuhan,China [2]Interdisciplinary Research Institute in New Finance and Economics(School of Digital Economics),Hubei University of Economics,Wuhan,China [3]Department of Sociology,Nankai University,Tianjin,China

出　　处：《The Journal of Chinese Sociology》2024年第1期510-533,共24页中国社会学杂志(英文)

基　　金：The National Social Science Fund project“Research on Social Emotion Risks and Governance of Online Cluster Events Based on Big Data”(22BSH024).

摘　　要：This paper focuses on the evolutionary mechanism of social emotions,such as panic,anxiety,and depression,during the COVID-19 pandemic by using big data from the internet,including Twitter and GDELT,and by incorporating factors related to risk communication and risk response in risk governance.The main negative emo-tions experienced during the COVID-19 pandemic include panic,anxiety,and depres-sion.These negative emotions primarily erupted on a large scale during the initial phase of the first wave of the epidemic,whereas the fluctuations in negative emotions during subsequent resurgences were significantly smaller.This paper explains the evo-lution of panic and depression through analytical frameworks based on threat percep-tion and coping efficacy,as well as social pressure and social support.The fluctuations in negative emotions around the world exhibit both similarities and diversities,which are closely related to the diversity of pandemic response models and cultural charac-teristics across different regions.The findings of this study have important implications for emergency management and the guidance of social mentality.

关 键 词：Big data Social emotions COVID-19 pandemic TWITTER GDELT 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]