Multimodal disinformation about otherness on the internet

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...

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Detalles Bibliográficos
Autores: Gamir-Ríos, José, Tarullo, Raquel|||0000-0003-2372-7571, Ibáñez-Cuquerella, Miguel
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:244249
Acceso en línea:https://ddd.uab.cat/record/244249
https://dx.doi.org/urn:doi:10.5565/rev/analisi.3398
Access Level:acceso abierto
Palabra clave:Disinformation
Social networks
Otherness
Racism
Xenophobia
Islamophobia
Desinformació
Xarxes socials
Alteritat
Racisme
Xenofòbia
Islamofòbia
Desinformación
Redes sociales
Otredad
Racismo
Xenofobia
Islamofobia
Descripción
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.