Polarización y similitud en las representaciones de mensajes oficiales en medios ante la pandemia de COVID-19
By using a triple machine learning approach, we conduct a content analysis on dos million bites of Mexican government information, and 28, 127 news and opinion columns published in 2020, relating to COVID pandemia. Findings report similarity in news and polarization in opinion columns. This means th...
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| Formatua: | Artikulua |
| Hizkuntza: | Gaztelania |
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2023
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| Sarrera elektronikoa: | https://dialnet.unirioja.es/servlet/oaiart?codigo=8913367 |
| Baliabidea: | Estudios en derecho a la información, ISSN 2683-2038, Nº. 16 (Julio-diciembre 2023), 202377 pags. |
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By using a triple machine learning approach, we conduct a content analysis on dos million bites of Mexican government information, and 28, 127 news and opinion columns published in 2020, relating to COVID pandemia. Findings report similarity in news and polarization in opinion columns. This means that news covered accurately Health General Council recommendations, but comments in media tended to distort what this group of professionals in Medicine provided with the objective of protect Mexicans’ lives. Those findings bring media social responsibility and right to information to the further discussions of COVID-19, the most serious health crisis in Mexico history. |
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