ArticleAmerican journal of infection control2018
Tweeting about measles during stages of an outbreak: A semantic network approach to the framing of an emerging infectious disease.
Article in American journal of infection control, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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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.
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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
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Social media based surveillance systems for healthcare using machine learning: A systematic review.Journal of biomedical informatics · 2020Pooled it
- The role of social media in public health crises caused by infectious disease: a scoping review.BMJ global health · 2023Article
- Sentiment Impact of Public Health Agency communication Strategies on TikTok under COVID-19 Normalization: Deep Learning Exploration.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2023Article
- Framing of COVID-19 in Newspapers: A Perspective from the US-Mexico Border.Healthcare (Basel, Switzerland) · 2022Article
- Exploring Public Perceptions of Dental Care Affordability in the United States: Mixed Method Analysis via Twitter.JMIR formative research · 2022Article
- Excavating the social representations and perceived barriers of organ donation in China over the past decade: A hybrid text analysis approach.Frontiers in public health · 2022Article
- Examining Crisis Communication Using Semantic Network and Sentiment Analysis: A Case Study on NetEase Games.Frontiers in psychology · 2022Article
- Coverage of Transmission of COVID-19 Information on Successive Samples of YouTube Videos.Journal of community health · 2021Article
- Verbalization, Categorization, and Evaluation of Fundamental Surgical Skills: An Expert Consensus in Open Head and Neck Surgery.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2021Article
- Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review.JMIR public health and surveillance · 2021Article
- Need for Interactive Data Visualization in Public Health Practice: Examples from India.International journal of preventive medicine · 2021Review
- Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak.Social network analysis and mining · 2021Article
- Structure of communities in semantic networks of biomedical research on disparities in health and sexismBiomedica : revista del Instituto Nacional de Salud · 2020Review
- Social Bots' Sentiment Engagement in Health Emergencies: A Topic-Based Analysis of the COVID-19 Pandemic Discussions on Twitter.International journal of environmental research and public health · 2020Article
- Tracking and Analyzing Public Emotion Evolutions During COVID-19: A Case Study from the Event-Driven Perspective on Microblogs.International journal of environmental research and public health · 2020Article
- Conversations and Misconceptions About Chemotherapy in Arabic Tweets: Content Analysis.Journal of medical Internet research · 2020Article
- A scoping review of the use of Twitter for public health research.Computers in biology and medicine · 2020Article
- Misinformation and the US Ebola communication crisis: analyzing the veracity and content of social media messages related to a fear-inducing infectious disease outbreak.BMC public health · 2020Article
- Article
- Curricular evaluation of "SHOKUIKU program" as a postgraduate minor course of food and nutrition education using a text-mining procedure.BMC nutrition · 2018Article
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
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe public increasingly uses social media not only to look for information about emerging infectious diseases (EIDs), but also to share opinions, emotions, and coping strategies. Identifying the frames used in social media discussion about EIDs will allow public health agencies to assess public opinions and sentiments.
methodThis study examined how the public discussed measles during the measles outbreak in the United States during early 2015 that originated in Disneyland Park in Anaheim, CA, through a semantic network analysis of the content of around 1 million tweets using KH coder.
resultsFour frames were identified based on word frequencies and co-occurrence: news update, public health, vaccination, and political. The prominence of each individual frame changed over the corse of the pre-crisis, initial, maintenance, and resolution stages of the outbreak.
conclusionsThis study proposed and tested a method for assessing the frames used in social media discussions about EIDs based on the creation, interpretation, and quantification of semantic networks. Public health agencies could use social media outlets, such as Twitter, to assess how the public makes sense of an EID outbreak and to create adaptive messages in communicating with the public during different stages of the crisis.
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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.