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A New Application of Social Impact in Social Media for Overcoming Fake News in Health

Autor(es):
Pulido, Cristina M | Ruiz-Eugenio, Laura | Redondo-Sama, Gisela | Villarejo-Carballido, Beatriz.
Editor: 2020Descripción: 1 documento pdf 74 kb.Tipo de contenido: texto (visual)
Tipo de medio: electrónico
Tipo de soporte: recurso en línea
Tema(s): eSalud | social media analysis | social impact in social media | public health | fake newsRecursos en línea: AbiertoAcceso al artículo Resumen: One of the challenges today is to face fake news (false information) in health due to its potential impact on people’s lives. This article contributes to a new application of social impact in social media (SISM) methodology. This study focuses on the social impact of the research to identify what type of health information is false and what type of information is evidence of the social impact shared in social media. The analysis of social media includes Reddit, Facebook, and Twitter. This analysis contributes to identifying how interactions in these forms of social media depend on the type of information shared. The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and finally, deliberation contexts promoted in social media overcome false information about health. These results contribute to advancing knowledge in overcoming fake health-related news shared in social media
Lista(s) en las que aparece este ítem: Fake news - Desinformación. Aprendizaje para reconocer noticias falsas | Nº 4. Novedades - Abril 2020 | Lo mejor del 2020
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Colección digital Acceso libre online .pdf 1000020176115

One of the challenges today is to face fake news (false information) in health due to its potential impact on people’s lives. This article contributes to a new application of social impact in social media (SISM) methodology. This study focuses on the social impact of the research to identify what type of health information is false and what type of information is evidence of the social impact shared in social media. The analysis of social media includes Reddit, Facebook, and Twitter. This analysis contributes to identifying how interactions in these forms of social media depend on the type of information shared. The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and finally, deliberation contexts promoted in social media overcome false information about health. These results contribute to advancing knowledge in overcoming fake health-related news shared in social media

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