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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34T/47NL3E2
Repositorysid.inpe.br/mtc-m21d/2022/10.03.13.48   (restricted access)
Last Update2022:10.03.13.48.06 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21d/2022/10.03.13.48.06
Metadata Last Update2023:01.03.16.46.19 (UTC) administrator
DOI10.3390/computation10090166
ISSN2079-3197
Citation KeyHarbSiAyViSiFr:2022:ApCOVa
TitleDendrograms for Clustering in Multivariate Analysis: Applications for COVID-19 Vaccination Infodemic Data in Brazil
Year2022
MonthSept.
Access Date2024, June 13
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size8332 KiB
2. Context
Author1 Harb, Maria da Penha
2 Silva, Lena
3 Ayass, Thalita
4 Vijaykumar, Nandamudi Lankalapalli
5 Silva, Marcelino
6 Frances, Carlos Renato
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JHTU
ORCID1 0000-0002-1873-143X
2
3
4 0000-0002-9025-0841
5 0000-0001-7504-7434
Group1
2
3
4 COPDT-CGIP-INPE-MCTI-GOV-BR
Affiliation1 Universidade Federal do Pará (UFPA)
2 Universidade do Amazonas
3 Universidade Federal do Pará (UFPA)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Universidade Federal do Oeste do Pará (UFOPA)
6 Universidade Federal do Pará (UFPA)
Author e-Mail Address1 mpenha@ufpa.br
2
3
4 vijaykumar.nandamudi@gmail.com
JournalComputation
Volume10
Number9
Pagese166
History (UTC)2022-10-03 13:49:08 :: simone -> administrator :: 2022
2023-01-03 16:46:19 :: administrator -> simone :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsdendrogram
infodemic
COVID-19
Google Trends
multivariate analysis
AbstractSince December 2019, with the discovery of a new coronavirus, humanity has been exposed to a large amount of information from different media. Information is not always true and official. Known as an infodemic, false information can increase the negative effects of the pandemic by impairing data readability and disease control. The paper aims to find similar patterns of behavior of the Brazilian population during 2021 in two analyses: with vaccination data of all age groups and using the age group of 64 years or more, representing 13% of the population, using the multivariate analysis technique. Infodemic vaccination information and pandemic numbers were also used. Dendrograms were used as a cluster visualization technique. The result of the generated clusters was verified by two algorithms: the cophenetic correlation coefficient, which obtained satisfactory results above 0.7, and the elbow method, which corroborated the number of clusters found. In the result of the analysis with all age groups, more homogeneous divisions were perceived among Brazilian states, while the second analysis resulted in more heterogeneous clusters, recalling that at the start of vaccinations they could have had fear, doubts, and significant belief in the infodemic.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > Dendrograms for Clustering...
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4. Conditions of access and use
Languageen
Target Filecomputation-10-00166.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46KUES5
Citing Item Listsid.inpe.br/bibdigital/2022/04.03.23.11 4
sid.inpe.br/mtc-m21/2012/07.13.14.56.50 3
DisseminationWEBSCI; PORTALCAPES; SCOPUS.
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
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