The role of emotion and social connection during the COVID-19 pandemic phase transitions: a cross-cultural comparison of China and the United States

Author:

Lu Liangdong,Xu Jia,Wei JiuchangORCID,Shults F. LeRonORCID,Feng Xing Lin

Abstract

AbstractLeveraging substantial data from China’s Weibo and datasets from Reddit and X (previously Twitter) in the United States, this research explores the disparities and complex dynamics of emotions and social connections among social media users in China and the United States during the COVID-19 pandemic. The findings indicate that the expression of three negative emotions (anxiety, sadness, and anger) and positive emotions exhibited distinctive dynamics under the impact of the pandemic, with China individuals expressing more anxiety but less sadness and anger than those in the US. Moreover, Chinese social media experienced a surge in positive emotional expressions under lockdown, whereas the US witnessed a conspicuous decline in positive emotions. Also, the expression of three types of social connections - “family”, “collective”, and “country”-exhibited significant differences under the impact of the pandemic, with Chinese individuals establishing deeper connections with their country and American individuals leaning towards familial connections. Further analysis on the moderating effects of social connections substantiated that the “country” connection in China and the “family” connection in the US mitigated the negative emotions affected by the pandemic. These findings facilitate a deeper understanding of how cultural contexts shape social and psychological responses in crises. Based on topic analysis and forward-looking orientation analysis, this study dissects the aforementioned findings through the dichotomy of collectivist and individualist cultures, providing new insights for social psychological support and emotional guidance in the development of public health communication strategies in the future.

Publisher

Springer Science and Business Media LLC

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1. Leveraging social media data for pandemic detection and prediction;Humanities and Social Sciences Communications;2024-08-23

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