Multimodal disinformation about otherness on the internet: the spread of racist, xenophobic and Islamophobic fake news in 2020
This work studies the use of disinformation to construct an image of otherness through the internet. We applied a content analysis methodology to the 161 racist, xenophobic or Islamophobic fake news pieces that were discredited in 2020 by the four Spanish information verification media entities accr...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/165987 |
| Acceso en línea: | http://hdl.handle.net/11336/165987 |
| Access Level: | acceso abierto |
| Palabra clave: | DISINFORMATION ISLAMOPHOBIA OTHERNESS RACISM SOCIAL NETWORKS XENOPHOBIA https://purl.org/becyt/ford/5.8 https://purl.org/becyt/ford/5 |
| Sumario: | This work studies the use of disinformation to construct an image of otherness through the internet. We applied a content analysis methodology to the 161 racist, xenophobic or Islamophobic fake news pieces that were discredited in 2020 by the four Spanish information verification media entities accredited by the International Fact-Checking Network: Maldita.es, Newtral, Efe Verifica and Verificat. The results show that the most commonly used formats were image and video, that disinformation was most often based on taking information out of context and deception, and that the source could not be identified. The most shared characteristics associated otherness with receiving aid, violence and illegal immigration. The most commonly used images were photographs, which mostly showed people in a general manner (not individually). Despite this, disinformation was not generated by manipulating images, but by inserting text over images. The use of supposed screenshots to create fictitious references or take truthful screenshots out of context was also notable. |
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