Evidence map›Paper›PMID 36554926›Full record

ArticleInternational journal of environmental research and public health2022

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

Sidemar Cezario, Thiago Marques, Rafael Pinto, Juciano Lacerda, Lyrene Silva, Thaisa Santos Lima, Orivaldo Santana, Anna Giselle Ribeiro, Agnaldo Cruz, Ana Claudia Araújo and 5 more

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Sidemar CezarioDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil.ORCID 0000-0001-9786-7134
Thiago MarquesDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil.ORCID 0000-0002-7652-4463
Rafael PintoDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil.ORCID 0000-0002-5051-2210
Juciano LacerdaLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.ORCID 0000-0002-0876-377X
Lyrene SilvaDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil.
Thaisa Santos LimaLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
Orivaldo SantanaLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.ORCID 0000-0003-4918-3162
Anna Giselle RibeiroLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.ORCID 0000-0001-8704-2868
Agnaldo CruzLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
Ana Claudia AraújoLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.ORCID 0000-0002-5128-6040
Angélica Espinosa MirandaMinistry of Health, Brasília 70070-600, Brazil.ORCID 0000-0002-5556-8379
Aedê CadaxaMinistry of Health, Brasília 70070-600, Brazil.
César TeixeiraDepartment of Informatics Engineering, Centre for Informatics and Systems of the University of Coimbra (CISUC), 3030-290 Coimbra, Portugal.
Almudena MuñozDepartment of Communication Theories and Analysis, Complutense University of Madrid, 28040 Madrid, Spain.ORCID 0000-0001-7513-081X
Ricardo ValentimLaboratory for Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.ORCID 0000-0002-9216-8593

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe "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.

methodsThis 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.

resultsHermes 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.

conclusionsThe 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.

Indexed as

EcosystemPublic HealthBrazilCommunicationMass Mediacommunicable diseasedata mininghealth policypublic healthsyphilistext extraction

Identifiers

PMID36554926
PMCPMC9778775

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.