ArticleJournal of medical Internet research2017
Public Response to Obamacare on Twitter.
Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
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- Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tips.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Grass-roots entrepreneurship complements traditional top-down innovation in lung and breast cancer.NPJ digital medicine · 2022Article
- A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion.Multimedia tools and applications · 2022Article
- Analyzing COVID-19 disinformation on Twitter using the hashtags #scamdemic and #plandemic: Retrospective study.PloS one · 2022Article
- Machine learning in medicine: a practical introduction to natural language processing.BMC medical research methodology · 2021Article
- 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
- Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter.Infection control and hospital epidemiology · 2021Article
- Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea.Journal of medical Internet research · 2020Article
- Sentiment Analysis in Health and Well-Being: Systematic Review.JMIR medical informatics · 2020Review
- How Do General-Purpose Sentiment Analyzers Perform when Applied to Health-Related Online Social Media Data?Studies in health technology and informatics · 2019Article
- Using Social Media Data to Understand the Impact of Promotional Information on Laypeople's Discussions: A Case Study of Lynch Syndrome.Journal of medical Internet research · 2017Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe Affordable Care Act (ACA), often called "Obamacare," is a controversial law that has been implemented gradually since its enactment in 2010. Polls have consistently shown that public opinion of the ACA is quite negative.
objectiveThe aim of our study was to examine the extent to which Twitter data can be used to measure public opinion of the ACA over time.
methodsWe prospectively collected a 10% random sample of daily tweets (approximately 52 million since July 2011) using Twitter's streaming application programming interface (API) from July 10, 2011 to July 31, 2015. Using a list of key terms and ACA-specific hashtags, we identified tweets about the ACA and examined the overall volume of tweets about the ACA in relation to key ACA events. We applied standard text sentiment analysis to assign each ACA tweet a measure of positivity or negativity and compared overall sentiment from Twitter with results from the Kaiser Family Foundation health tracking poll.
resultsPublic opinion on Twitter (measured via sentiment analysis) was slightly more favorable than public opinion measured by the Kaiser poll (approximately 50% vs 40%, respectively) but trends over time in both favorable and unfavorable views were similar in both sources. The Twitter-based measures of opinion as well as the Kaiser poll changed very little over time: correlation coefficients for favorable and unfavorable public opinion were .43 and .37, respectively. However, we found substantial spikes in the volume of ACA-related tweets in response to key events in the law's implementation, such as the first open enrollment period in October 2013 and the Supreme Court decision in June 2012.
conclusionsTwitter may be useful for tracking public opinion of health care reform as it appears to be comparable with conventional polling results. Moreover, in contrast with conventional polling, the overall amount of tweets also provides a potential indication of public interest of a particular issue at any point in time.
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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.