Modelagem de tópicos de pesquisa sobre o novo coronavírus: aplicação do Latent Dirichlet Allocation

Tatiane Baratieri; Maicon Henrique Lentsck; Clérito Kaveski Peres; Erica  de Brito Pitilin

doi:10.4025/ciencuidsaude.v20i0.56403

Tatiane Baratieri Universidade Estadual do Centro-Oeste - UNICENTRO https://orcid.org/0000-0002-0270-6395
Maicon Henrique Lentsck Universidade Estadual do Centro-Oeste https://orcid.org/0000-0002-8912-8902
Clérito Kaveski Peres Universidade Federal de Santa Catarina https://orcid.org/0000-0002-5643-6888
Erica de Brito Pitilin Universidade Federal da Fronteira Sul http://orcid.org/0000-0003-3950-2633

DOI: https://doi.org/10.4025/ciencuidsaude.v20i0.56403

Keywords: Coronavirus infections, COVID-19, Pandemics, Review

Abstract

Objective: to analyze the global development of scientific publications and build topics covered in research on the new coronavirus/COVID-19. Methods: review of abstracts of publications on the new coronavirus/COVID-19 with search in the Embase and Web of Science databases, on November 3, 2020. Data were analyzed by modeling the research topics using Latent Dirichlet Allocation (LDA) method. Results: a total of 31,769 publications were analyzed, involving researchers from 182 countries. The studies were published in 5,336 different journals. The analysis identified 20 main research topics on the new coronavirus/COVID-19, with more than half (54.5%) covering topics of impacts and challenges resulting from the pandemic (11.3%), immune response (9.6%), potential therapies (9.0%), epidemiology (7.8%), mental health (6.3%), recommendations for assistance with other health needs (5.3%), and clinical complications. The theme of telemedicine and telehealth was present in 4.2% of publications. Conclusions: scientific publications were distributed among 20 main themes, characterizing their importance and relevance in understanding the disease in question to outline strategies for control, prevention, treatment and attention to diseases/implications resulting from the pandemic. Studies on primary care measures/primary health care were identified as the main knowledge gap.

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Author Biographies

Tatiane Baratieri, Universidade Estadual do Centro-Oeste - UNICENTRO

Enfermeira. Doutora. Departamento do Enfermagem da Universidade Estadual do Centro-Oeste – UNICENTRO. Guarapuava, Paraná, Brasil.

Maicon Henrique Lentsck, Universidade Estadual do Centro-Oeste

Enfermeiro. Doutor. Departamento do Enfermagem da UNICENTRO. . Guarapuava, Paraná, Brasil.

Clérito Kaveski Peres, Universidade Federal de Santa Catarina

Engenheiro de Produção. Mestre. Doutorando pelo Programa de Pós-Graduação em Engenharia de Produção da Universidade Federal de Santa Catarina – UFSC. Florianópolis, Santa Catarina, Brasil.

Erica de Brito Pitilin, Universidade Federal da Fronteira Sul

Enfermeira. Doutora. Departamento de Enfermagem da Universidade Federal da Fronteira Sul. Chapecó, Santa Catarina, Brasil.

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Modeling of research topics on the new coronavirus: application of Latent Dirichlet Allocation

Abstract

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References