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Similarity Analysis in Understanding Online News in Response to Public Health Crisis

Author

Listed:
  • Sidemar Cezario

    (Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil)

  • Thiago Marques

    (Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil)

  • Rafael Pinto

    (Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil
    Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    Information Systems Coordination, Federal Institute of Rio Grande do Norte, Natal 59015-300, Brazil)

  • Juciano Lacerda

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    Department of Social Communication, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil)

  • Lyrene Silva

    (Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil)

  • Thaisa Santos Lima

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    Federal Senate, Brasília 70165-900, Brazil)

  • Orivaldo Santana

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    School of Science and Technology, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil)

  • Anna Giselle Ribeiro

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    School of Science and Technology, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil)

  • Agnaldo Cruz

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil)

  • Ana Claudia Araújo

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    Department of Social Communication, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil)

  • Angélica Espinosa Miranda

    (Ministry of Health, Brasília 70070-600, Brazil
    Postgraduate Program in Infectious Diseases, Federal University of Espírito Santo, Vitória 29075-910, Brazil)

  • Aedê Cadaxa

    (Ministry of Health, Brasília 70070-600, Brazil)

  • César Teixeira

    (Department of Informatics Engineering, Centre for Informatics and Systems of the University of Coimbra (CISUC), 3030-290 Coimbra, Portugal)

  • Almudena Muñoz

    (Department of Communication Theories and Analysis, Complutense University of Madrid, 28040 Madrid, Spain)

  • Ricardo Valentim

    (Laboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil
    Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal 59628-330, Brazil)

Abstract

Background: The “Syphilis No!” campaign the Brazilian Ministry of Health (MoH) launched between November 2018 and March 2019, brought forward the concept "Test, Treat and Cure" to remind the population of the importance of syphilis prevention. In this context, this study aims to analyze the similarity of syphilis online news to comprehend how public health communication interventions influence media coverage of the syphilis issue. Methods: This paper presented a computational approach to assess the effectiveness of communication actions on a public health problem. Data were collected between January 2015 and December 2019 and processed using the Hermes ecosystem, which utilizes text mining and machine learning algorithms to cluster similar content. Results: Hermes identified 1049 google-indexed web pages containing the term ’syphilis’ in Brazil. Of these, 619 were categorized as news stories. In total, 157 were grouped into clusters of at least two similar news items and a single cluster with 462 news classified as “single” for not featuring similar news items. From these, 19 clusters were identified in the pre-campaign period, 23 during the campaign, and 115 in the post-campaign. Conclusions: The findings presented in this study show that the volume of syphilis-related news reports has increased in recent years and gained popularity after the SNP started, having been boosted during the campaign and escalating even after its completion.

Suggested Citation

  • Sidemar Cezario & Thiago Marques & Rafael Pinto & Juciano Lacerda & Lyrene Silva & Thaisa Santos Lima & Orivaldo Santana & Anna Giselle Ribeiro & Agnaldo Cruz & Ana Claudia Araújo & Angélica Espinosa , 2022. "Similarity Analysis in Understanding Online News in Response to Public Health Crisis," IJERPH, MDPI, vol. 19(24), pages 1-14, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:17049-:d:1007619
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    References listed on IDEAS

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