ArticleJournal of biomedical semantics2011
OMG U got flu? Analysis of shared health messages for bio-surveillance.
Article in Journal of biomedical semantics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 4 of them syntheses that pooled it.
What it found
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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.
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
44 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025Pooled it
- Social media and outbreaks of emerging infectious diseases: A systematic review of literature.American journal of infection control · 2018Pooled it
- Mapping of Crowdsourcing in Health: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Attitudes Toward the Ethics of Research Using Social Media: A Systematic Review.Journal of medical Internet research · 2017Pooled it
- Tweeting links to Cochrane Schizophrenia Group reviews: a randomised controlled trial.BMJ open · 2016Trial
- To tweet or not to tweet about schizophrenia systematic reviews (TweetSz): study protocol for a randomised controlled trial.BMJ open · 2015Trial
- Public Social Media Discussions on Agricultural Product Safety Incidents: Chinese African Swine Fever Debate on Weibo.Frontiers in psychology · 2022Article
- Re-evaluating standards of human subjects protection for sensitive health data in social media networks.Social networks · 2021Article
- Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review.Yearbook of medical informatics · 2021Review
- Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases.NPJ digital medicine · 2021Article
- Social Media and Health Care, Part I: Literature Review of Social Media Use by Health Care Providers.Journal of medical Internet research · 2021Review
- Ethical Considerations for Participatory Health through Social Media: Healthcare Workforce and Policy Maker Perspectives.Yearbook of medical informatics · 2020Article
- Extracting health-related causality from twitter messages using natural language processing.BMC medical informatics and decision making · 2019Article
- Article
- The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations.Child abuse & neglect · 2018Article
- Can online social support be detrimental in stigmatized chronic diseases? A quadratic model of the effects of informational and emotional support on self-care behavior of HIV patients.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Disease mentions in airport and hospital geolocations expose dominance of news events for disease concerns.Journal of biomedical semantics · 2018Article
- Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text.Yearbook of medical informatics · 2017Review
- Identifying personal health experience tweets with deep neural networks.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2017Article
- Saúde na Copa: The World's First Application of Participatory Surveillance for a Mass Gathering at FIFA World Cup 2014, Brazil.JMIR public health and surveillance · 2017Article
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
backgroundMicro-blogging services such as Twitter offer the potential to crowdsource epidemics in real-time. However, Twitter posts ('tweets') are often ambiguous and reactive to media trends. In order to ground user messages in epidemic response we focused on tracking reports of self-protective behaviour such as avoiding public gatherings or increased sanitation as the basis for further risk analysis.
resultsWe created guidelines for tagging self protective behaviour based on Jones and Salathé (2009)'s behaviour response survey. Applying the guidelines to a corpus of 5283 Twitter messages related to influenza like illness showed a high level of inter-annotator agreement (kappa 0.86). We employed supervised learning using unigrams, bigrams and regular expressions as features with two supervised classifiers (SVM and Naive Bayes) to classify tweets into 4 self-reported protective behaviour categories plus a self-reported diagnosis. In addition to classification performance we report moderately strong Spearman's Rho correlation by comparing classifier output against WHO/NREVSS laboratory data for A(H1N1) in the USA during the 2009-2010 influenza season.
conclusionsThe study adds to evidence supporting a high degree of correlation between pre-diagnostic social media signals and diagnostic influenza case data, pointing the way towards low cost sensor networks. We believe that the signals we have modelled may be applicable to a wide range of diseases.
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.