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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/7448| QUANTITATIVE ANALYSIS OF VISUAL REPRESENTATION OF SIGN ELEMENTS IN COVID-19 CONTEXT | |
| María Jesús Cano Martínez Miguel Carrasco César González-Martín Joaquín Sandoval | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| arXiv:2112.08219 | |
| https://arxiv.org/abs/2112.08219 | |
| Representation is the way in which human beings re-present the reality of what is happening, both externally and internally. Thus, visual representation as a means of communication uses elements to build a narrative, just as spoken and written language do. We propose using computer analysis to perform a quantitative analysis of the elements used in the visual creations that have been produced in reference to the epidemic, using the images compiled in The Covid Art Museum's Instagram account to analyze the different elements used to represent subjective experiences with regard to a global event. This process has been carried out with techniques based on machine learning to detect objects in the images so that the algorithm can be capable of learning and detecting the objects contained in each study image. This research reveals that the elements that are repeated in images to create narratives and the relations of association that are established in the sample, concluding that, despite the subjectivity that all creation entails, there are certain parameters of shared and reduced decisions when it comes to selecting objects to be included in visual representations | |
| Cornell University | |
| 15-12-2021 | |
| Preimpreso | |
| arxiv.org | |
| Inglés | |
| Epidemia COVID-19 | |
| Investigadores Público en general | |
| OTRAS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Artículos científicos |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Quantitative Analysis of Visual Representation of Sign Elements in COVID 19 context.pdf | 10.24 MB | Adobe PDF | Visualizar/Abrir |