ArticleInfection control and hospital epidemiology2021
Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter.
Article in Infection control and hospital epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Birds of a feather? Mis- and dis-information on the social media platform X related to avian influenza.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025Article
- A National Discussion of COVID-19 on Twitter.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024Article
- Analysis of Pharmaceutical Companies' Social Media Activity during the COVID-19 Pandemic and Its Impact on the Public.Behavioral sciences (Basel, Switzerland) · 2024Article
- A pandemic of COVID-19 mis- and disinformation: manual and automatic topic analysis of the literature.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2024Article
- Twitter discussions on breastfeeding during the COVID-19 pandemic.International breastfeeding journal · 2023Article
- Psychological and psychosocial determinants of COVID Health Related Behaviours (COHeRe): An evidence and gap map.Campbell systematic reviews · 2023Article
- [Sentiments in the COVID-19 crisis communication of German authorities and independent experts on Twitter : A sentiment analysis for the first year of the pandemic].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2023Article
- Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis.Journal of medical Internet research · 2023Article
- Analyzing an Emerging Pandemic on Twitter: Monkeypox.Open forum infectious diseases · 2023Article
- The Association of a Geographically Wide Social Media Network on Depression: County-Level Ecological Analysis.Journal of medical Internet research · 2023Article
- The Voice of the Patient and the Electronic Health Record.Applied clinical informatics · 2023Article
- A global portrait of expressed mental health signals towards COVID-19 in social media space.International journal of applied earth observation and geoinformation : ITC journal · 2023Article
- Sentiment Analysis on Twitter: Role of Healthcare Professionals in the Global Conversation during the AstraZeneca Vaccine Suspension.International journal of environmental research and public health · 2023Article
- Reaching Populations at Risk for HIV Through Targeted Facebook Advertisements: Cost-Consequence Analysis.JMIR formative research · 2023Article
- Estimating time-series changes in social sentiment @Twitter in U.S. metropolises during the COVID-19 pandemic.Journal of computational social science · 2023Article
- "Is a game really a reason for people to die?" Sentiment and thematic analysis of Twitter-based discourse on Indonesia soccer stampede.AIMS public health · 2023Article
- Sentiment analysis using Twitter data: a comparative application of lexicon- and machine-learning-based approach.Social network analysis and mining · 2023Article
- Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis.Journal of medical Internet research · 2022Article
- The Politicization of Ivermectin Tweets During the COVID-19 Pandemic.Open forum infectious diseases · 2022Article
- A prediction model with measured sentiment scores for the risk of in-hospital mortality in acute pancreatitis: a retrospective cohort study.Annals of translational medicine · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveSocial distancing policies are key in curtailing severe acute respiratory coronavirus virus 2 (SARS-CoV-2) spread, but their effectiveness is heavily contingent on public understanding and collective adherence. We studied public perception of social distancing through organic, large-scale discussion on Twitter.
designRetrospective cross-sectional study.
methodsBetween March 27 and April 10, 2020, we retrieved English-only tweets matching two trending social distancing hashtags, #socialdistancing and #stayathome. We analyzed the tweets using natural language processing and machine-learning models, and we conducted a sentiment analysis to identify emotions and polarity. We evaluated the subjectivity of tweets and estimated the frequency of discussion of social distancing rules. We then identified clusters of discussion using topic modeling and associated sentiments.
resultsWe studied a sample of 574,903 tweets. For both hashtags, polarity was positive (mean, 0.148; SD, 0.290); only 15% of tweets had negative polarity. Tweets were more likely to be objective (median, 0.40; IQR, 0-0.6) with ~30% of tweets labeled as completely objective (labeled as 0 in range from 0 to 1). Approximately half of tweets (50.4%) primarily expressed joy and one-fifth expressed fear and surprise. Each correlated well with topic clusters identified by frequency including leisure and community support (ie, joy), concerns about food insecurity and quarantine effects (ie, fear), and unpredictability of coronavirus disease 2019 (COVID-19) and its implications (ie, surprise).
conclusionsConsidering the positive sentiment, preponderance of objective tweets, and topics supporting coping mechanisms, we concluded that Twitter users generally supported social distancing in the early stages of their implementation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.