Understanding belief in political statements using a model-driven experimental approach: a registered report

Autores
Perez Santangelo, Agustin; Solovey, Guillermo
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Misinformation harms society by affecting citizens´ beliefs and behaviour. Recent research has shown that partisanship and cognitive reflection (i.e. engaging in analytical thinking) play key roles in the acceptance of misinformation. However, the relative importance of these factors remains a topic of ongoing debate. In this registered study, we tested four hypotheses on the relationship between each factor and the belief in statements made by Argentine politicians. Participants (N = 1353) classified fact-checked political statements as true or false, completed a cognitive reflection test, and reported their voting preferences. Using Signal Detection Theory and Bayesian modeling, we found a reliable positive association between political concordance and overall belief in a statement (median = 0.663, CI95 = [0.640, 0.685]), a reliable positive association between cognitive reflection and scepticism (median = 0.039, CI95 = [0.006, 0.072]), a positive but unreliable association between cognitive reflection and truth discernment (median = 0.016, CI95 = [− 0.015, 0.046]) and a positive but unreliable association between cognitive reflection and partisan bias (median = 0.016, CI95 = [− 0.006, 0.037]). Our results highlight the need to further investigate the relationship between cognitive reflection and partisanship in different contexts and formats.
Fil: Perez Santangelo, Agustin. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Solovey, Guillermo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Materia
SIGNAL DETECTION THEORY
MISINFORMATION
BAYESIAN MODELS
STATISTICS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/248832
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Understanding belief in political statements using a model-driven experimental approach: a registered reportPerez Santangelo, AgustinSolovey, GuillermoSIGNAL DETECTION THEORYMISINFORMATIONBAYESIAN MODELSSTATISTICShttps://purl.org/becyt/ford/1.7https://purl.org/becyt/ford/1Misinformation harms society by affecting citizens´ beliefs and behaviour. Recent research has shown that partisanship and cognitive reflection (i.e. engaging in analytical thinking) play key roles in the acceptance of misinformation. However, the relative importance of these factors remains a topic of ongoing debate. In this registered study, we tested four hypotheses on the relationship between each factor and the belief in statements made by Argentine politicians. Participants (N = 1353) classified fact-checked political statements as true or false, completed a cognitive reflection test, and reported their voting preferences. Using Signal Detection Theory and Bayesian modeling, we found a reliable positive association between political concordance and overall belief in a statement (median = 0.663, CI95 = [0.640, 0.685]), a reliable positive association between cognitive reflection and scepticism (median = 0.039, CI95 = [0.006, 0.072]), a positive but unreliable association between cognitive reflection and truth discernment (median = 0.016, CI95 = [− 0.015, 0.046]) and a positive but unreliable association between cognitive reflection and partisan bias (median = 0.016, CI95 = [− 0.006, 0.037]). Our results highlight the need to further investigate the relationship between cognitive reflection and partisanship in different contexts and formats.Fil: Perez Santangelo, Agustin. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Solovey, Guillermo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaNature2023-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/248832Perez Santangelo, Agustin; Solovey, Guillermo; Understanding belief in political statements using a model-driven experimental approach: a registered report; Nature; Scientific Reports; 13; 1; 1-12-2023; 1-202045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-023-47939-3info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-023-47939-3#citeasinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:01:36Zoai:ri.conicet.gov.ar:11336/248832instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:01:37.182CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Understanding belief in political statements using a model-driven experimental approach: a registered report
title Understanding belief in political statements using a model-driven experimental approach: a registered report
spellingShingle Understanding belief in political statements using a model-driven experimental approach: a registered report
Perez Santangelo, Agustin
SIGNAL DETECTION THEORY
MISINFORMATION
BAYESIAN MODELS
STATISTICS
title_short Understanding belief in political statements using a model-driven experimental approach: a registered report
title_full Understanding belief in political statements using a model-driven experimental approach: a registered report
title_fullStr Understanding belief in political statements using a model-driven experimental approach: a registered report
title_full_unstemmed Understanding belief in political statements using a model-driven experimental approach: a registered report
title_sort Understanding belief in political statements using a model-driven experimental approach: a registered report
dc.creator.none.fl_str_mv Perez Santangelo, Agustin
Solovey, Guillermo
author Perez Santangelo, Agustin
author_facet Perez Santangelo, Agustin
Solovey, Guillermo
author_role author
author2 Solovey, Guillermo
author2_role author
dc.subject.none.fl_str_mv SIGNAL DETECTION THEORY
MISINFORMATION
BAYESIAN MODELS
STATISTICS
topic SIGNAL DETECTION THEORY
MISINFORMATION
BAYESIAN MODELS
STATISTICS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.7
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Misinformation harms society by affecting citizens´ beliefs and behaviour. Recent research has shown that partisanship and cognitive reflection (i.e. engaging in analytical thinking) play key roles in the acceptance of misinformation. However, the relative importance of these factors remains a topic of ongoing debate. In this registered study, we tested four hypotheses on the relationship between each factor and the belief in statements made by Argentine politicians. Participants (N = 1353) classified fact-checked political statements as true or false, completed a cognitive reflection test, and reported their voting preferences. Using Signal Detection Theory and Bayesian modeling, we found a reliable positive association between political concordance and overall belief in a statement (median = 0.663, CI95 = [0.640, 0.685]), a reliable positive association between cognitive reflection and scepticism (median = 0.039, CI95 = [0.006, 0.072]), a positive but unreliable association between cognitive reflection and truth discernment (median = 0.016, CI95 = [− 0.015, 0.046]) and a positive but unreliable association between cognitive reflection and partisan bias (median = 0.016, CI95 = [− 0.006, 0.037]). Our results highlight the need to further investigate the relationship between cognitive reflection and partisanship in different contexts and formats.
Fil: Perez Santangelo, Agustin. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Solovey, Guillermo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
description Misinformation harms society by affecting citizens´ beliefs and behaviour. Recent research has shown that partisanship and cognitive reflection (i.e. engaging in analytical thinking) play key roles in the acceptance of misinformation. However, the relative importance of these factors remains a topic of ongoing debate. In this registered study, we tested four hypotheses on the relationship between each factor and the belief in statements made by Argentine politicians. Participants (N = 1353) classified fact-checked political statements as true or false, completed a cognitive reflection test, and reported their voting preferences. Using Signal Detection Theory and Bayesian modeling, we found a reliable positive association between political concordance and overall belief in a statement (median = 0.663, CI95 = [0.640, 0.685]), a reliable positive association between cognitive reflection and scepticism (median = 0.039, CI95 = [0.006, 0.072]), a positive but unreliable association between cognitive reflection and truth discernment (median = 0.016, CI95 = [− 0.015, 0.046]) and a positive but unreliable association between cognitive reflection and partisan bias (median = 0.016, CI95 = [− 0.006, 0.037]). Our results highlight the need to further investigate the relationship between cognitive reflection and partisanship in different contexts and formats.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/248832
Perez Santangelo, Agustin; Solovey, Guillermo; Understanding belief in political statements using a model-driven experimental approach: a registered report; Nature; Scientific Reports; 13; 1; 1-12-2023; 1-20
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/248832
identifier_str_mv Perez Santangelo, Agustin; Solovey, Guillermo; Understanding belief in political statements using a model-driven experimental approach: a registered report; Nature; Scientific Reports; 13; 1; 1-12-2023; 1-20
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-023-47939-3
info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-023-47939-3#citeas
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature
publisher.none.fl_str_mv Nature
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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