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Sentiment Analysis in Understanding the Potential of Online News in the Public Health Crisis Response.
Marques, Thiago; Cezário, Sidemar; Lacerda, Juciano; Pinto, Rafael; Silva, Lyrene; Santana, Orivaldo; Ribeiro, Anna Giselle; Cruz, Agnaldo Souza; Miranda, Angélica Espinosa; Cadaxa, Aedê; Núñez, Lucía Sanjuán; Gonçalo Oliveira, Hugo; Atun, Rifat; Valentim, Ricardo.
Afiliação
  • Marques T; Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.
  • Cezário S; Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.
  • Lacerda J; Department of Social Communication, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil.
  • Pinto R; Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
  • Silva L; Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.
  • Santana O; Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
  • Ribeiro AG; Information Systems Coordination, Federal Institute of Rio Grande do Norte, Natal 59015-300, Brazil.
  • Cruz AS; Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.
  • Miranda AE; Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
  • Cadaxa A; School of Science and Technology, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.
  • Núñez LS; Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
  • Gonçalo Oliveira H; Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
  • Atun R; Ministry of Health, Brasília 70070-600, Brazil.
  • Valentim R; Postgraduate Program in Infectious Diseases, Federal University of Espírito Santo, Vitória 29075-910, Brazil.
Article em En | MEDLINE | ID: mdl-36554680
ABSTRACT
This study analyzes online news disseminated throughout the pre-, during-, and post-intervention periods of the "Syphilis No!" Project, which was developed in Brazil between November 2018 and March 2019. We investigated the influence of sentiment aspects of news to explore their possible relationships with syphilis testing data in response to the syphilis epidemic in Brazil. A dictionary-based technique (VADER) was chosen to perform sentiment analysis considering the Brazilian Portuguese language. Finally, the data collected were used in statistical tests to obtain other indicators, such as correlation and distribution analysis. Of the 627 news items, 198 (31.58%) were classified as a sentiment of security (TP2; stands for the news type 2), whereas 429 (68.42%) were classified as sentiments that instilled vulnerability (TP3; stands for the news type 3). The correlation between the number of syphilis tests and the number of news types TP2 and TP3 was verified from (i) 2015 to 2017 and (ii) 2018 to 2019. For the TP2 type news, in all periods, the p-values were greater than 0.05, thus generating inconclusive results. From 2015 to 2017, there was an ρ = 0.33 correlation between TP3 news and testing data (p-value = 0.04); the years 2018 and 2019 presented a ρ = 0.67 correlation between TP3 news and the number of syphilis tests performed per month, with p-value = 0.0003. In addition, Granger's test was performed between TP3 news and syphilis testing, which resulted in a p-value = 0.002, thus indicating the existence of Granger causality between these time series. By applying natural language processing to sentiment and informational content analysis of public health campaigns, it was found that the most substantial increase in testing was strongly related to attitude-inducing content (TP3).
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Sífilis / Epidemias / Mídias Sociais Limite: Humans Idioma: En Revista: Int J Environ Res Public Health Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Sífilis / Epidemias / Mídias Sociais Limite: Humans Idioma: En Revista: Int J Environ Res Public Health Ano de publicação: 2022 Tipo de documento: Article