Twitter Voices: Twitter Users’ Sentiments and Emotions About COVID-19 Vaccination within the United States

When asked if she would go to the White House if invited, Megan Rapinoe stated, “I’m not going to the fucking White House.” The next morning, President Donald Trump posted a series of tweets in which he criticized Rapinoe’s statements. In his tweets, Trump introduced issues around race in the United States and brought forth his own notion of nationalism. The purpose of this study was to conduct an analysis of users’ tweets to determine how individuals employed Twitter to craft a narrative and discuss the ongoing Rapinoe and Trump feud within and outside the bounds of Critical Race Theory (CRT) and nationalism. An inductive analysis of 16,137 users’ tweets revealed three primary themes: a) Refuse, Refute, & Redirect Racist Rhetoric b) Stand Up vs. Know your Rights, and c) #ShutUpAndBeALeader. Based on the findings of this study, it appears that the dialogue regarding racism in the United States is quickly evolving. Instead of reciting the same refrain (i.e., racism no longer exists and systematic racism is constructed by Black people) seen in previous works, individuals in the current dataset refuted those talking points and clearly labeled the President as a racist. Additionally, though discussions of nationalism were evident in this dataset, the Stand Up vs. Know Your Rights theme was on the periphery in comparison to discussions of race. Perhaps, this indicates that some have grown tired of Trump utilizing nationalism as a means to stoke racism.

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A Study of the Effects of the COVID-19 Pandemic on the Experience of Back Pain Reported on Twitter® in the United States: A Natural Language Processing Approach

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094543 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4543

Author(s):

Krzysztof Fiok ◽

Waldemar Karwowski ◽

Edgar Gutierrez ◽

Maham Saeidi ◽

Awad M. Aljuaid ◽

...

Keyword(s):

United States ◽

Natural Language Processing ◽

Back Pain ◽

Natural Language ◽

Language Processing ◽

The United States ◽

Daily Routine ◽

Body Movements ◽

Data Source ◽

Twitter Users

The COVID-19 pandemic has changed our lifestyles, habits, and daily routine. Some of the impacts of COVID-19 have been widely reported already. However, many effects of the COVID-19 pandemic are still to be discovered. The main objective of this study was to assess the changes in the frequency of reported physical back pain complaints reported during the COVID-19 pandemic. In contrast to other published studies, we target the general population using Twitter as a data source. Specifically, we aim to investigate differences in the number of back pain complaints between the pre-pandemic and during the pandemic. A total of 53,234 and 78,559 tweets were analyzed for November 2019 and November 2020, respectively. Because Twitter users do not always complain explicitly when they tweet about the experience of back pain, we have designed an intelligent filter based on natural language processing (NLP) to automatically classify the examined tweets into the back pain complaining class and other tweets. Analysis of filtered tweets indicated an 84% increase in the back pain complaints reported in November 2020 compared to November 2019. These results might indicate significant changes in lifestyle during the COVID-19 pandemic, including restrictions in daily body movements and reduced exposure to routine physical exercise.

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The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States

10.1101/2021.08.23.21262489 ◽

2021 ◽

Cited By ~ 1

Author(s):

Senqi Zhang ◽

Li Sun ◽

Daiwei Zhang ◽

Pin Li ◽

Yue Liu ◽

...

Keyword(s):

Mental Health ◽

United States ◽

Topic Modeling ◽

The United States ◽

Allocation Model ◽

Health Concerns ◽

Demographic Composition ◽

The Us ◽

Mental Health Concerns ◽

Twitter Users

AbstractBackgroundMental health illness is a growing problem in recent years. During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media.ObjectiveIn this study, we aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the United States and infer the demographic composition of Twitter users who had mental health concerns.MethodsCOVID-19 related tweets from March 5th, 2020 to January 31st, 2021 were collected through Twitter streaming API using COVID-19 related keywords (e.g., “corona”, “covid19”, “covid”). By further filtering using mental health keywords (e.g., “depress”, “failure”, “hopeless”), we extracted mental health-related tweets from the US. Topic modeling using the Latent Dirichlet Allocation model was conducted to monitor users’ discussions surrounding mental health concerns. Demographic inference using deep learning algorithms (including Face++ and Ethnicolr) was performed to infer the demographic composition of Twitter users who had mental health concerns during the COVID-19 pandemic.ResultsWe observed a positive correlation between mental health concerns on Twitter and the COVID-19 pandemic in the US. Topic modeling showed that “stay-at-home”, “death poll” and “politics and policy” were the most popular topics in COVID-19 mental health tweets. Among Twitter users who had mental health concerns during the pandemic, Males, White, and 30-49 age group people were more likely to express mental health concerns. In addition, Twitter users from the east and west coast had more mental health concerns.ConclusionsThe COVID-19 pandemic has a significant impact on mental health concerns on Twitter in the US. Certain groups of people (such as Males, White) were more likely to have mental health concerns during the COVID-19 pandemic.

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Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

JMIR Infodemiology ◽

10.2196/25636 ◽

2021 ◽

Vol 1 (1) ◽

pp. e25636

Author(s):

Li Crystal Jiang ◽

Tsz Hang Chu ◽

Mengru Sun

Keyword(s):

United States ◽

Topic Modeling ◽

Vaccine Development ◽

Close Association ◽

Negative Emotions ◽

The United States ◽

Conspiracy Theories ◽

Early Stages ◽

Twitter Users ◽

Public Concerns

Background During the early stages of the COVID-19 pandemic, developing safe and effective coronavirus vaccines was considered critical to arresting the spread of the disease. News and social media discussions have extensively covered the issue of coronavirus vaccines, with a mixture of vaccine advocacies, concerns, and oppositions. Objective This study aimed to uncover the emerging themes in Twitter users’ perceptions and attitudes toward vaccines during the early stages of the COVID-19 outbreak. Methods This study employed topic modeling to analyze tweets related to coronavirus vaccines at the start of the COVID-19 outbreak in the United States (February 21 to March 20, 2020). We created a predefined query (eg, “COVID” AND “vaccine”) to extract the tweet text and metadata (number of followers of the Twitter account and engagement metrics based on likes, comments, and retweeting) from the Meltwater database. After preprocessing the data, we tested Latent Dirichlet Allocation models to identify topics associated with these tweets. The model specifying 20 topics provided the best overall coherence, and each topic was interpreted based on its top associated terms. Results In total, we analyzed 100,209 tweets containing keywords related to coronavirus and vaccines. The 20 topics were further collapsed based on shared similarities, thereby generating 7 major themes. Our analysis characterized 26.3% (26,234/100,209) of the tweets as News Related to Coronavirus and Vaccine Development, 25.4% (25,425/100,209) as General Discussion and Seeking of Information on Coronavirus, 12.9% (12,882/100,209) as Financial Concerns, 12.7% (12,696/100,209) as Venting Negative Emotions, 9.9% (9908/100,209) as Prayers and Calls for Positivity, 8.1% (8155/100,209) as Efficacy of Vaccine and Treatment, and 4.9% (4909/100,209) as Conspiracies about Coronavirus and Its Vaccines. Different themes demonstrated some changes over time, mostly in close association with news or events related to vaccine developments. Twitter users who discussed conspiracy theories, the efficacy of vaccines and treatments, and financial concerns had more followers than those focused on other vaccine themes. The engagement level—the extent to which a tweet being retweeted, quoted, liked, or replied by other users—was similar among different themes, but tweets venting negative emotions yielded the lowest engagement. Conclusions This study enriches our understanding of public concerns over new vaccines or vaccine development at early stages of the outbreak, bearing implications for influencing vaccine attitudes and guiding public health efforts to cope with infectious disease outbreaks in the future. This study concluded that public concerns centered on general policy issues related to coronavirus vaccines and that the discussions were considerably mixed with political views when vaccines were not made available. Only a small proportion of tweets focused on conspiracy theories, but these tweets demonstrated high engagement levels and were often contributed by Twitter users with more influence.

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#MaskOn! #MaskOff! Digital polarization of mask-wearing in the United States during COVID-19

PLoS ONE ◽

10.1371/journal.pone.0250817 ◽

2021 ◽

Vol 16 (4) ◽

pp. e0250817

Author(s):

Jun Lang ◽

Wesley W. Erickson ◽

Zhuo Jing-Schmidt

Keyword(s):

United States ◽

Public Opinion ◽

Media Coverage ◽

Temporal Trends ◽

The United States ◽

Political Polarization ◽

Health Crisis ◽

Verbal Representation ◽

Twitter Users ◽

The One

The coronavirus disease 2019 (COVID-19) has caused an unprecedented public health crisis worldwide. Its intense politicization constantly made headlines, especially regarding the use of face masks as a safety precaution. However, the extent to which public opinion is polarized on wearing masks has remained anecdotal and the verbal representation of this polarization has not been explored. This study examined the types, themes, temporal trends, and exchange patterns of hashtags about mask wearing posted from March 1 to August 1, 2020 by Twitter users based in the United States. On the one hand, we found a stark rhetorical polarization in terms of semantic antagonism between pro- and anti-mask hashtags, exponential frequency increases of both types of hashtags during the period under study, in parallel to growing COVID-19 case counts, state mask mandates, and media coverage. On the other hand, the results showed an asymmetric participatory polarization in terms of a predominance of pro-mask hashtags along with an “echo chamber” effect in the dominant pro-mask group, which ignored the subversive rhetoric of the anti-mask minority. Notwithstanding the limitations of the research, this study provides a nuanced account of the digital polarization of public opinion on mask wearing. It draws attention to political polarization both as a rhetorical phenomenon and as a participatory process.

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Limited Role of Bots in Spreading Vaccine-Critical Information Among Active Twitter Users in the United States: 2017–2019

American Journal of Public Health ◽

10.2105/ajph.2020.305902 ◽

2020 ◽

Vol 110 (S3) ◽

pp. S319-S325 ◽

Cited By ~ 1

Author(s):

Adam G. Dunn ◽

Didi Surian ◽

Jason Dalmazzo ◽

Dana Rezazadegan ◽

Maryke Steffens ◽

...

Keyword(s):

United States ◽

Confidence Interval ◽

Odds Ratio ◽

The United States ◽

Median Number ◽

Critical Information ◽

Critical Content ◽

Twitter Users ◽

Vaccine Information

Objectives. To examine the role that bots play in spreading vaccine information on Twitter by measuring exposure and engagement among active users from the United States. Methods. We sampled 53 188 US Twitter users and examined who they follow and retweet across 21 million vaccine-related tweets (January 12, 2017–December 3, 2019). Our analyses compared bots to human-operated accounts and vaccine-critical tweets to other vaccine-related tweets. Results. The median number of potential exposures to vaccine-related tweets per user was 757 (interquartile range [IQR] = 168–4435), of which 27 (IQR = 6–169) were vaccine critical, and 0 (IQR = 0–12) originated from bots. We found that 36.7% of users retweeted vaccine-related content, 4.5% retweeted vaccine-critical content, and 2.1% retweeted vaccine content from bots. Compared with other users, the 5.8% for whom vaccine-critical tweets made up most exposures more often retweeted vaccine content (62.9%; odds ratio [OR] = 2.9; 95% confidence interval [CI] = 2.7, 3.1), vaccine-critical content (35.0%; OR = 19.0; 95% CI = 17.3, 20.9), and bots (8.8%; OR = 5.4; 95% CI = 4.7, 6.3). Conclusions. A small proportion of vaccine-critical information that reaches active US Twitter users comes from bots.

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Diversification and Nuanced Inequities in Digital Media Use in the United States

Digital Multimedia ◽

10.4018/978-1-5225-3822-6.ch058 ◽

2018 ◽

pp. 1216-1237

Author(s):

Eliane Rubinstein-Avila ◽

Aurora Sartori

Keyword(s):

United States ◽

Digital Media ◽

Race And Ethnicity ◽

High Speed ◽

The United States ◽

Confounding Factors ◽

Culturally Specific ◽

Twitter Users ◽

Digital Exclusion ◽

Roll Out

This chapter explores access to, and engagement with, digital media by United States' (U.S.) by nonmainstream populations. Framing the issue from a sociotechnical standpoint, the authors explore how engagement with digital media is shaped by socioeconomic status (taking into account confounding factors, such as race and ethnicity, and social and geographical ecologies). The authors highlight studies that focus on the robust digital practices with which nonmainstream populations already engage, and to which they contribute. One example is how some black Twitter users engage in signifyin'–a culturally specific linguistic practice—as a means of performing racial identity online. The authors also problematize concepts such as the new digital divide and digital exclusion, and finally, reiterate that a universal roll-out of high speed broadband alone will not necessarily lead to further engagement with digital media for ALL populations. In fact, the authors claim that providing more or faster access is likely not enough to prevent the entrenchment of a global digital underclass.

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Counter-hegemonic contra-flow and the Al Jazeera America fiasco: A social network analysis of Al Jazeera America’s Twitter users

Global Media and Communication ◽

10.1177/1742766517734255 ◽

2017 ◽

Vol 13 (3) ◽

pp. 267-282 ◽

Cited By ~ 3

Author(s):

Tal Samuel-Azran ◽

Tsahi Hayat

Keyword(s):

United States ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

The United States ◽

Selective Exposure ◽

Al Jazeera ◽

The West ◽

Twitter Users ◽

News Outlet

Al Jazeera America, arguably the most ambitious attempt in history by a non-Western network to broadcast to US audiences, was shut in April 2016. A social network analysis of Al Jazeera America’s following on Twitter reveals that 42 per cent of Al Jazeera America’s followers did not follow any other US news outlet and that most of the remaining 58 per cent followed liberal stations. The findings illustrate mainstream US news consumers’ reluctance to follow Al Jazeera America, which only appealed to specific audiences. The analysis portrays the challenges facing counter-hegemonic contra-flow stations such as Al Jazeera America in their bid to gain legitimacy in the West, and specifically in the United States, and highlights the relevance of selective exposure and hostile media theories in the case of counter-flowing stations.

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Public Reactions towards the COVID-19 Pandemic on Twitter in the United Kingdom and the United States

10.1101/2020.07.25.20162024 ◽

2020 ◽

Author(s):

Canruo Zou ◽

Xueting Wang ◽

Zidian Xie ◽

Dongmei Li

Keyword(s):

United States ◽

United Kingdom ◽

Topic Modeling ◽

Health Workers ◽

The United States ◽

The Public ◽

The United Kingdom ◽

Twitter Data ◽

Media Platform ◽

Twitter Users

Background: The coronavirus disease 2019 (COVID-19) has spread globally since December 2019. Twitter is a popular social media platform with active discussions about the COVID-19 pandemic. The public reactions on Twitter about the COVID-19 pandemic in different countries have not been studied. This study aims to compare the public reactions towards the COVID-19 pandemic between the United Kingdom and the United States from March 6, 2020 to April 2, 2020. Data: The numbers of confirmed COVID-19 cases in the United Kingdom and the United States were obtained from the 1Point3Acres website. Twitter data were collected using COVID-19 related keywords from March 6, 2020 to April 2, 2020. Methods: Temporal analyses were performed on COVID-19 related Twitter posts (tweets) during the study period to show daily trends and hourly trends. The sentiment scores of the tweets on COVID-19 were analyzed and associated with the policy announcements and the number of confirmed COVID-19 cases. Topic modeling was conducted to identify related topics discussed with COVID-19 in the United Kingdom and the United States. Results: The number of daily new confirmed COVID-19 cases in the United Kingdom was significantly lower than that in the United States during our study period. There were 3,556,442 COVID-19 tweets in the United Kingdom and 16,280,065 tweets in the United States during the study period. The number of COVID-19 tweets per 10,000 Twitter users in the United Kingdom was lower than that in the United States. The sentiment scores of COVID-19 tweets in the United Kingdom were less negative than those in the United States. The topics discussed in COVID-19 tweets in the United Kingdom were mostly about the gratitude to government and health workers, while the topics in the United States were mostly about the global COVID-19 pandemic situation. Conclusion: Our study showed correlations between the public reactions towards the COVID-19 pandemic on Twitter and the confirmed COVID-19 cases as well as the policies related to the COVID-19 pandemic in the United Kingdom and the United States.

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Sustained Online Amplification of COVID-19 Elites in the United States

Social Media + Society ◽

10.1177/20563051211024957 ◽

2021 ◽

Vol 7 (2) ◽

pp. 205630512110249

Author(s):

Ryan J. Gallagher ◽

Larissa Doroshenko ◽

Sarah Shugars ◽

David Lazer ◽

Brooke Foucault Welles

Keyword(s):

Public Health ◽

United States ◽

Health Information ◽

The United States ◽

First Year ◽

Public Health Information ◽

Small Set ◽

Twitter Users ◽

Vaccine Distribution ◽

Political Alignment

In the absence of clear, consistent guidelines about the COVID-19 pandemic in the United States, many people use social media to learn about the virus, public health directives, vaccine distribution, and other health information. As people individually sift through a flood of information online, they collectively curate a small set of accounts, known as crowdsourced elites, that receive disproportionate attention for their COVID-19 content. However, these elites are not all created equal: not all accounts have received the same attention during the pandemic, and various demographic and ideological groups have crowdsourced their own elites. Using a mixed-methods approach with a panel of Twitter users in the United States over the first year of the COVID-19 pandemic, we identify COVID-19 crowdsourced elites. We distinguish sustained amplification from episodic amplification and demonstrate that crowdsourced elites vary across demographics with respect to race, geography, and political alignment. Specifically, we show that different subpopulations preferentially amplify elites that are demographically similar to them, and that they crowdsource different types of elite accounts, such as journalists, elected officials, and medical professionals, in different proportions. In light of this variation, we discuss the potential for using the disproportionate online voice of crowdsourced COVID-19 elites to equitably promote public health information and mitigate misinformation across networked publics.

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