June 2, 2021 Dataset Open Access

Bienvenido León; Pilar Martínez-Costa; Ramón Salaverría; Ignacio López-Goñi

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    "description": "<p>This dataset contains the coding of content analysis of a sample of&nbsp;hoaxes debunked by three fact checkers in Spain&nbsp;(N = 533): Maldita.es (N = 327), Newtral (N = 143), and EFE Verifica (N = 63). Coding includes de following variables:</p>\n\n<p>&nbsp; &nbsp; &nbsp; &nbsp;0. Subject of the hoax: science/health, politics/government, other.&nbsp;</p>\n\n<ol>\n\t<li>Platform used to spread the hoax: networks (in general), Twitter, Facebook, WhatsApp, Instagram, YouTube, and others.</li>\n\t<li>Formats used: text, audio, image, video, other.</li>\n\t<li>Geographical scope: local, national, international, unspecified/not applicable.</li>\n\t<li>Type of hoax: joke, exaggeration, decontextualization, deception.</li>\n\t<li>Topic of hoaxes related to science/health: scientific research, scientific policy and health management, advice issued to the public, and others.</li>\n\t<li>Topic of hoaxes related to scientific research: origin of the virus, transmissibility, fatality rate, treatments, vaccines, etc.</li>\n\t<li>Source type: anonymous, spoofed, fictitious, real.</li>\n\t<li>Non-anonymous sources: members of the public, business, government, professional, healthcare/science.</li>\n\t<li>Type of healthcare/science sources: researchers, international scientific organizations, national scientific organizations, health professionals, and others.</li>\n</ol>", 
    "language": "spa", 
    "title": "Content analysis dataset of health and science-related hoaxes during COVID-19 in Spain", 
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        "name": "Bienvenido Le\u00f3n"
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        "affiliation": "University of Navarra", 
        "name": "Pilar Mart\u00ednez-Costa"
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