Automatically quantifying the scientific quality and sensationalism of news records mentioning pandemics: validating a maximum entropy machine-learning model

OBJECTIVE: To develop and validate a method for automatically quantifying the scientific quality and sensationalism of individual news records. STUDY DESIGN: After retrieving 163,433 news records mentioning the Severe Acute Respiratory Syndrome (SARS) and H1N1 pandemics, a maximum entropy model for...

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Detalles Bibliográficos
Autores principales: Hoffman, Steven J., Justicz, Victoria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2016
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7127105/
https://www.ncbi.nlm.nih.gov/pubmed/26854419
http://dx.doi.org/10.1016/j.jclinepi.2015.12.010

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7127105/
https://www.ncbi.nlm.nih.gov/pubmed/26854419
http://dx.doi.org/10.1016/j.jclinepi.2015.12.010

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