Tracking and Analyzing Public Emotion Evolutions During COVID-19: A Case Study from the Event-Driven Perspective on Microblogs

Abstract

Objective: Coronavirus disease 2019 (COVID-19) has caused substantial panic worldwide since its outbreak in December 2019. This study uses social networks to track the evolution of public emotion during COVID-19 in China and analyzes the root causes of these public emotions from an event-driven perspective. Methods: A dataset was constructed using microblogs (n = 125,672) labeled with COVID-19-related super topics (n = 680) from 40,891 users from 1 December 2019 to 17 February 2020. Based on the skeleton and key change points of COVID-19 extracted from microblogging contents, we tracked the public’s emotional evolution modes (accumulated emotions, emotion covariances, and emotion transitions) by time phase and further extracted the details of dominant social events. Results: Public emotions showed different evolution modes during different phases of COVID-19. Events about the development of COVID-19 remained hot, but generally declined, and public attention shifted to other aspects of the epidemic (e.g., encouragement, support, and treatment). Conclusions: These findings suggest that the public’s feedback on COVID-19 predated official accounts on the microblog platform. There were clear differences in the trending events that large users (users with many fans and readings) and common users paid attention to during each phase of COVID-19.

Capturing the Trajectory of Psychological Status and Analyzing Online Public Reactions During the Coronavirus Disease 2019 Pandemic Through Weibo Posts in China

“…The public psychological status differed among different periods of the COVID-19 pandemic; this result was consistent with other studies (Li Q. et al, 2020 ; Li Y. et al, 2020 ; Zhao et al, 2020 ; Yin et al, 2021 ). This study also illustrated the decline of pessimistic sentiment during the regular epidemic prevention and control period, which has also been revealed by other scholars (Jia and Liu, 2021 ).…”

“…Positive emotions were higher than negative emotions in that period. During this period, public attention shifted to other aspects of the pandemic, and public opinions primarily expressed praise for the pandemic control achievements and tributes to healthcare workers of China (Li Q. et al, 2020 ). In addition, the results of this study showed that the newly confirmed cases of COVID-19 were related to changes in public psychological status and had an almost 1-month lag effect on public sentiment.…”

The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment Based on System Dynamics and Cross-Validation

“…A Twitter analysis of Chinese Netizen sentiment during COVID-19 found that Chinese Netizens’ sentiment was consistently negative, but increased slightly as the outbreak subsided [ 51 ]. In addition, many similar studies on Chinese microblogs (WeiBo, Sina, Beijing, China) have found similar results [ 52 , 53 ]. These studies were able to provide evidence for our results.…”

Twitter Users’ Displays of Affect in the Global Warming Debate

“…In terms of methods, many studies (Fersini et al, 2016;Fung et al, 2016;Gaspar et al, 2016;Mohammad & Kiritchenko, 2015;Saif et al, 2016) use keyword counting and manual categorization to find user emotions and sentiment on Twitter. Other studies (Do et al, 2016;Hasan et al, 2014;Q. Li et al, 2020) rely on computational methods, and some use a combination of both computational and manual methods (Chung & Zeng, 2020).…”