ArticleHealth data science2021
Characterizing Discourse about COVID-19 Vaccines: A Reddit Version of the Pandemic Story.
Article in Health data science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review.JMIR public health and surveillance · 2023Pooled it
- Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing.Scientific reports · 2023Article
- Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects.Computers in human behavior · 2023Article
- Article
- Human behavior in the time of COVID-19: Learning from big data.Frontiers in big data · 2023Review
- Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis.Journal of medical Internet research · 2022Article
- Doctors vs. Nurses: Understanding the Great Divide in Vaccine Hesitancy among Healthcare Workers.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2022Article
- Impact of COVID-19 Vaccine Misinformation on Social Media Virality: Content Analysis of Message Themes and Writing Strategies.Journal of medical Internet research · 2022Article
- Using Deep Learning to Identify Linguistic Features that Facilitate or Inhibit the Propagation of Anti- and Pro-Vaccine Content on Social Media.IEEE International Conference on Digital Health. IEEE International Conference on Digital Health · 2022Article
- COVID-19 vaccine perceptions in the initial phases of US vaccine roll-out: an observational study on reddit.BMC public health · 2022Observational
- Social media study of public opinions on potential COVID-19 vaccines: informing dissent, disparities, and dissemination.Intelligent medicine · 2022Article
- Misinformation versus Facts: Understanding the Influence of News regarding COVID-19 Vaccines on Vaccine Uptake.Health data science · 2022Article
- Does the COVID-19 Vaccine Still Work That "Most of the Confirmed Cases Had Been Vaccinated"? A Content Analysis of Vaccine Effectiveness Discussion on Sina Weibo during the Outbreak of COVID-19 in Nanjing.International journal of environmental research and public health · 2021Article
- Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence.Journal of infection and public health · 2021Article
- Social Media Opinions on Working From Home in the United States During the COVID-19 Pandemic: Observational Study.JMIR medical informatics · 2021Article
- A comparative analysis of anti-vax discourse on twitter before and after COVID-19 onset.Health informatics journalArticle
- Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study.JMIR infodemiologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
It has been one year since the outbreak of the COVID-19 pandemic. The good news is that vaccines developed by several manufacturers are being actively distributed worldwide. However, as more and more vaccines become available to the public, various concerns related to vaccines become the primary barriers that may hinder the public from getting vaccinated. Considering the complexities of these concerns and their potential hazards, this study is aimed at offering a clear understanding about different population groups' underlying concerns when they talk about COVID-19 vaccines-particularly those active on Reddit. The goal is achieved by applying LDA and LIWC to characterize the pertaining discourse with insights generated through a combination of quantitative and qualitative comparisons. Findings include the following: (1) during the pandemic, the proportion of Reddit comments predominated by conspiracy theories outweighed that of any other topics; (2) each subreddit has its own user bases, so information posted in one subreddit may not reach that from other subreddits; and (3) since users' concerns vary across time and subreddits, communication strategies must be adjusted according to specific needs. The results of this study manifest challenges as well as opportunities in the process of designing effective communication and immunization programs.
Identifiers
What 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.