Evidence map›Paper›PMID 36554680›Full record

ArticleInternational journal of environmental research and public health2022

Sentiment Analysis in Understanding the Potential of Online News in the Public Health Crisis Response.

Thiago Marques, Sidemar Cezário, Juciano Lacerda, Rafael Pinto, Lyrene Silva, Orivaldo Santana, Anna Giselle Ribeiro, Agnaldo Souza Cruz, Angélica Espinosa Miranda, Aedê Cadaxa and 4 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 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

14 authors.

Thiago MarquesDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0002-7652-4463
Sidemar CezárioDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0001-9786-7134
Juciano LacerdaDepartment of Social Communication, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil.ORCID 0000-0002-0876-377X
Rafael PintoDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.
Lyrene SilvaDepartment of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0003-1772-6062
Orivaldo SantanaLaboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.ORCID 0000-0003-4918-3162
Anna Giselle RibeiroLaboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
Agnaldo Souza CruzLaboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte, Natal 59010-090, Brazil.
Angélica Espinosa MirandaMinistry of Health, Brasília 70070-600, Brazil.ORCID 0000-0002-5556-8379
Aedê CadaxaMinistry of Health, Brasília 70070-600, Brazil.ORCID 0000-0001-6600-7422
Lucía Sanjuán NúñezDepartment of Social and Cultural Anthropology, Autonomous University of Barcelona, 08193 Barcelona, Spain.ORCID 0000-0002-3206-7061
Hugo Gonçalo OliveiraCentre for Informatics and Systems of the University of Coimbra (CISUC), Department of Informatics Engineering (DEI), University of Coimbra, 3030-290 Coimbra, Portugal.ORCID 0000-0002-5779-8645
Rifat AtunHealth Systems Innovation Laboratory, Harvard TH Chan School Public Health, Harvard University, Boston, MA 02115, USA.
Ricardo ValentimLaboratory of 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

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

Indexed as

EpidemicsSocial MediaSyphilisHumansPublic HealthSentiment AnalysisTime Factorsdigital solutiononline newspublic healthpublic policysentiment analysis

Identifiers

PMID36554680
PMCPMC9779517

What OpenQuestion holds

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Registered trials

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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.