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

  • Carolina Luquea [1] ; Juan Rubriche [1] ; Jhon Galvis [1] ; Juan Sosa [1]
    1. [1] Universidad Santo Tomas, Colombia
  • Localización: Comunicaciones en Estadística, ISSN 2027-3355, ISSN-e 2339-3076, Vol. 14, Nº. 2, 2021, págs. 48-66
  • Idioma: español
  • DOI: 10.15332/23393076.7705
  • Títulos paralelos:
    • Topic modeling to identify patterns in Covid-19 scientific research
  • Enlaces
  • Resumen
    • español

      Presentamos un modelo de t ́opicos basado en el m ́etodo asignaci ́on latente de Di-richlet (LDA, por sus siglas en ingl ́es) con el objetivo de examinar patrones en lainvestigaci ́on cient ́ıfica del Covid–19 teniendo en cuenta las publicaciones indexa-das en la base datos especializada PubMed. Se toman 4928 resumenes cient ́ıficospublicados durante el primer semestre de 2020. Se ajusta un modelo LDA utili-zando dos t ́opicos. El primer t ́opico corresponde a factores de riesgo, severidad ymortalidad por infecci ́on viral, mientras que el segundo al impacto de las infeccio-nes respiratorias en la salud p ́ublica. La clasificaci ́on propuesta brinda una visi ́onglobal sobre las dos tendencias de investigaci ́on presentes a la fecha en la que elan ́alisis tiene lugar. Adicionalmente, los resultados se ̃nalan que la aplicaci ́on de lametodolog ́ıa propuesta provee un camino para direccionar y hacer m ́as eficiente larevisi ́on bibliogr ́afica en el contexto acad ́emico.

    • English

      We consider a topic modeling approach using latent Dirichlet allocation (LDA)methods aiming to examine patterns in the scientific research of Covid-19 usingpublications indexed in the PubMed database. A total of 4928 scientific abstractspublished during the first semester of 2020 are taken into account. An LDA mo-del is fitted using two topics. The first topic corresponds to risk factors, severity, and mortality due to viral infection, whereas the second is the impact of respi-ratory illnesses on public health. Our classification provides a global overview ofthese two research trends from the moment the analysis takes place. Additionally,our findings suggest that the systematic application of the proposed methodologyprovides a way to address and make more efficient the bibliographic review inacademic contexts.

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