Modelamiento de tópicos para identificar patrones en la investigación cientíifica del Covid-19

Autores/as

  • Carolina Luque
  • Juan Carlos Rubriche
  • Jhon Galvis
  • Juan Sosa

Palabras clave:

Covid-19, modelos de tópicos, asignación latente de Dirichlet, bases biliográficas, PubMed

Resumen

Presentamos un modelo de tópicos basado en el método asignación latente de Dirichlet (LDA, por sus siglas en inglés) con el objetivo de examinar patrones en la investigación científica del Covid--19 teniendo en cuenta las publicaciones indexadas en la base datos especializada PubMed. Se toman 4928 resumenes científicos publicados durante el primer semestre de 2020. Se ajusta un modelo LDA utilizando dos tópicos. El primer tópico corresponde a factores de riesgo, severidad y mortalidad por infección viral, mientras que el segundo al impacto de las infecciones respiratorias en la salud pública. La clasificación propuesta brinda una visión global sobre las dos tendencias de investigación presentes a la fecha en la que el análisis tiene lugar. Adicionalmente, los resultados señalan que la aplicación de la metodología propuesta provee un camino para direccionar y hacer más eficiente la revisión bibliográfica en el contexto académico.

Citas

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Publicado

2021-12-01

Cómo citar

Luque Zabala, C. M., Rubriche Cárdenas, J. C., Galvis, J. J., & Sosa, J. C. (2021). Modelamiento de tópicos para identificar patrones en la investigación cientíifica del Covid-19. Comunicaciones En Estadística, 14(2), 48–66. Recuperado a partir de https://revistas.usantotomas.edu.co/index.php/estadistica/article/view/7705

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