Interdisciplinary Studies

Rise and fall of the global conversation and shifting sentiments during the COVID-19 pandemic

X. Zhang, Q. Yang, et al.

This fascinating study reveals insights from over 105 million tweets and Weibo messages during the COVID-19 pandemic. Conducted by a team of experts, including Xiangliang Zhang and Qiang Yang, the research uncovers the emotional journey through a mix of joking and negativity, eventually leading to a rise in positive emotions as the situation improved.

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Playback language: English

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Abstract

This study analyzed over 105 million tweets and Weibo messages from March 1 to May 15, 2020, across six languages (English, Spanish, Arabic, French, Italian, and Chinese), to examine the emotional landscape of the COVID-19 pandemic. Using deep learning models, the researchers identified various emotional expressions (positive, negative, and joking). The analysis revealed a rapid rise and slow decline in conversation volume, triggered by economic collapse and confinement measures. Similar emotional patterns emerged across languages, with a mix of joking and negative emotions initially, followed by an increase in positive emotions as the pandemic subsided.

Publisher

Humanities & Social Sciences Communications

Published On

May 17, 2021

Authors

Xiangliang Zhang, Qiang Yang, Somayah Albaradei, Xiaoting Lyu, Hind Alamro, Adil Salhi, Changsheng Ma, Manal Alshehri, Inji Ibrahim Jaber, Faroug Tifratene, Wei Wang, Takashi Gojobori, Carlos M. Duarte, Xin Gao

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