ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ethical and Methodological Considerations of Twitter Data for Public Health Research: Systematic Review.Journal of medical Internet research · 2022Pooled it
- DomainDemo: a dataset of domain-sharing activities among different demographic groups on Twitter.Scientific data · 2025Article
- Factors influencing college students' online rumor refuting behavior during major public health crises: the moderating effect of group norms.Frontiers in psychology · 2024Article
- Article
- Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China.Computers in human behavior · 2023Article
- The impact of Public Health Emergency (PHE) on the news dissemination strength: Evidence from Chinese-Speaking Vloggers on YouTube.PloS one · 2023Article
- Microblog data analysis of emotional reactions to COVID-19 in China.Journal of psychosomatic research · 2022Article
- Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis.Pathogens (Basel, Switzerland) · 2022Review
- Sentiment analysis of COVID-19 social media data through machine learning.Multimedia tools and applications · 2022Article
- Analysis of social media data for public emotion on the Wuhan lockdown event during the COVID-19 pandemic.Computer methods and programs in biomedicine · 2021Article
- Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review.Yearbook of medical informatics · 2021Review
- Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Miscommunication in the age of communication: A crowdsourcing framework for symptom surveillance at the time of pandemics.International journal of medical informatics · 2021Article
- Promoting Public Engagement during the COVID-19 Crisis: How Effective Is the Wuhan Local Government's Information Release?International journal of environmental research and public health · 2020Article
- Article
- Grappling With the COVID-19 Health Crisis: Content Analysis of Communication Strategies and Their Effects on Public Engagement on Social Media.Journal of medical Internet research · 2020Article
- Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.Journal of medical systems · 2020Review
- Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts.Journal of medical Internet research · 2020Article
- Chinese Public's Attention to the COVID-19 Epidemic on Social Media: Observational Descriptive Study.Journal of medical Internet research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social media are important platforms for risk communication during public health crises. Effective dissemination of accurate, relevant, and up-to-date health information is important for the public to raise awareness and develop risk management strategies. This study investigates Zika virus-related information circulated on Twitter, identifying the patterns of dissemination of popular tweets and tweets from public health authorities such as the CDC. We leveraged a large corpus of Twitter data covering the entire year of 2016. We analyzed the data using quantitative and qualitative content analyses, followed by machine learning to scale the manual content analyses to the corpus. The results revealed possible discrepancies between what the general public was most interested in, or concerned about, and what public health authorities provided during the Zika outbreak. We provide implications for public health authorities to improve risk communication through better alignment with the general public's information needs during public health crises.
Indexed as
Identifiers
29854148PMC5977662What OpenQuestion holds
Registered trials
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.