Anatomy into the battle of supporting or opposing reopening amid the COVID-19 pandemic on Twitter: A temporal and spatial analysis

Li, Lingyao; Erfani, Abdolmajid; Wang, Yu; Cui, Qingbin

doi:10.1371/journal.pone.0254359

Cited by 15 publications

(9 citation statements)

References 46 publications

(68 reference statements)

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“…However, despite their promising potentials, these kinds of data are relatively underlooked in the existing scholarly literature. Saleh et al [ 56 ] as well as Oyebode and coworkers [ 57 ] and Li and colleagues [ 58 ], confirming our findings, reported that a significant portion of tweets and posts on social networkers expressed fear of the societal implications of the COVID-19 pandemic, conveying worries and concerns for the loss of income, unemployment, inflation, and financial burden/hardship.…”

Section: Discussionsupporting

confidence: 89%

A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments

et al. 2022

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The COVID-19 pandemic has had a devastating impact on the global economy. In this paper, we use the Phillips curve to compare and analyze the macroeconomics of three different countries with distinct income levels, namely, lower-middle (Nigeria), upper-middle (South Africa), and high (Canada) income. We aim to (1) find macroeconomic changes in the three countries during the pandemic compared to pre-pandemic time, (2) compare the countries in terms of response to the COVID-19 economic crisis, and (3) compare their expected economic reaction to the COVID-19 pandemic in the near future. An advantage to our work is that we analyze macroeconomics on a monthly basis to capture the shocks and rapid changes caused by on and off rounds of lockdowns. We use the volume and social sentiments of the Twitter data to approximate the macroeconomic statistics. We apply four different machine learning algorithms to estimate the unemployment rate of South Africa and Nigeria on monthly basis. The results show that at the beginning of the pandemic the unemployment rate increased for all the three countries. However, Canada was able to control and reduce the unemployment rate during the COVID-19 pandemic. Nonetheless, in line with the Phillips curve short-run, the inflation rate of Canada increased to a level that has never occurred in more than fifteen years. Nigeria and South Africa have not been able to control the unemployment rate and did not return to the pre-COVID-19 level. Yet, the inflation rate has increased in both countries. The inflation rate is still comparable to the pre-COVID-19 level in South Africa, but based on the Phillips curve short-run, it will increase further, if the unemployment rate decreases. Unfortunately, Nigeria is experiencing a horrible stagflation and a wild increase in both unemployment and inflation rates. This shows how vulnerable lower-middle-income countries could be to lockdowns and economic restrictions. In the near future, the main concern for all the countries is the high inflation rate. This work can potentially lead to more targeted and publicly acceptable policies based on social media content.

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Section: Discussionsupporting

confidence: 89%

A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments

et al. 2022

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“…Different from previous research conclusions on the single development of emotional changes [ 16 ], we found that the positive emotions and negative emotions of social media users affected by China’s sudden opening-up policy are different in the inflection point of emotional evolution and the performance of events of concern.…”

Section: Discussioncontrasting

confidence: 99%

“…Such studies show that large numbers of citizens express support for reopening lockdown policies but express emotional concerns about their implementation [ 15 ]. This is a contradictory emotional expression that requires specific analysis of the factors that generate user emotions [ 16 ]. There are studies analyzing the characteristics and influencing factors of Twitter users’ emotions towards the reopening of the economy [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the evolving factors of social media users’ emotions and behaviors: a longitudinal study from China’s COVID-19 opening policy period

Zhang,

Yang,

Niu

et al. 2023

BMC Public Health

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The outbreak of the COVID-19 pandemic has triggered citizen panic and social crises worldwide. The Chinese government was the first to implement strict prevention and control policies. However, in December 2022, the Chinese government suddenly changed its prevention and control policies and completely opened up. This led to a large-scale infection of the epidemic in a short period of time, which will cause unknown social impacts. This study collected 500+ epidemic-related hotspots and 200,000+ data from November 1, 2022, to March 1, 2023. Using a sentiment classification method based on pre-trained neural network models, we conducted inductive analysis and a summary of high-frequency words of various emotions. This study focuses on the inflection point of the emotional evolution of social media users and the evolution of “hot topic searches” events and emotional behavioral factors after the sudden open policy. Our research results show that, first of all, the positive emotions of social media users are divided into 4 inflection points and 5 time periods, and the negative emotions are divided into 3 inflection points and 4 time periods. Behavioral factors are different at each stage of each emotion. And the evolution patterns of positive emotions and negative emotions are also different. Secondly, the evolution of behavioral elements deserves more attention. Continue to pay attention: The treatment of diseases, the recovery of personal health, the promotion of festive atmosphere, and the reduction of publicity on the harm of “new crown sequelae and second infections” are the behavioral concerns that affect users’ emotional changes. Finally, it is necessary to change the “hot topic searches” event by guiding the user’s behavioral focus to control the inflection point of the user’s emotion. This study helps governments and institutions understand the dynamic impact of epidemic policy changes on social media users, thereby promoting policy formulation and better coping with social crises.

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“…In this study, we sought to understand public emotional responses by county to public health policies implemented in the early weeks of the COVID-19 pandemic. Other studies have examined state-level public perceptions regarding support or opposition [16]. A better understanding of the public's emotional response to policies at the county level may offer important insights for policymakers as they consider how to tailor implementation and communication strategies in their areas and the spillover effects of their efforts in surrounding communities.…”

Section: Discussionmentioning

confidence: 99%

“…Scholars have utilized social media data to gauge the collective reactions of the public and study responses to various policy interventions [12][13][14]. Researchers have also studied Twitter 9.0 data to understand disinformation during the pandemic [15] and support for and opposition to reopening policies [16].…”

Section: Introductionmentioning

confidence: 99%

Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S

Gao,

Gallegos,

West

2023

IJERPH

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Social networks, particularly Twitter 9.0 (known as X as of 23 July 2023), have provided an avenue for prompt interactions and sharing public health-related concerns and emotions, especially during the COVID-19 pandemic when in-person communication became less feasible due to stay-at-home policies in the United States (U.S.). The study of public emotions extracted from social network data has garnered increasing attention among scholars due to its significant predictive value for public behaviors and opinions. However, few studies have explored the associations between public health policies, local political ideology, and the spatial-temporal trends of emotions extracted from social networks. This study aims to investigate (1) the spatial-temporal clustering trends (or spillover effects) of negative emotions related to COVID-19; and (2) the association relationships between public health policies such as stay-at-home policies, political ideology, and the negative emotions related to COVID-19. This study employs multiple statistical methods (zero-inflated Poisson (ZIP) regression, random-effects model, and spatial autoregression (SAR) model) to examine relationships at the county level by using the data merged from multiple sources, mainly including Twitter 9.0, Johns Hopkins, and the U.S. Census Bureau. We find that negative emotions related to COVID-19 extracted from Twitter 9.0 exhibit spillover effects, with counties implementing stay-at-home policies or leaning predominantly Democratic showing higher levels of observed negative emotions related to COVID-19. These findings highlight the impact of public health policies and political polarization on spatial-temporal public emotions exhibited in social media. Scholars and policymakers can benefit from understanding how public policies and political ideology impact public emotions to inform and enhance their communication strategies and intervention design during public health crises such as the COVID-19 pandemic.

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Anatomy into the battle of supporting or opposing reopening amid the COVID-19 pandemic on Twitter: A temporal and spatial analysis

Cited by 15 publications

References 46 publications

A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments

A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments

Analysis of the evolving factors of social media users’ emotions and behaviors: a longitudinal study from China’s COVID-19 opening policy period

Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S

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