Epistemic Overconfidence in Algorithmic News Selection

Detalhes bibliográficos
Autor(a) principal: van der Velden, Mariken
Data de Publicação: 2021
Outros Autores: Loecherbach, Felicia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.17645/mac.v9i4.4167
Resumo: The process of news consumption has undergone great changes over the past decade: Information is now available in an ever-increasing amount from a plethora of sources. Recent work suggests that most people would favor algorithmic solutions over human editors. This stands in contrast to public and scholarly debate about the pitfalls of algorithmic news selection—i.e., the so-called “filter bubbles.” This study therefore investigates reasons and motivations which might lead people to prefer algorithmic gatekeepers over human ones. We expect that people have more algorithmic appreciation when consuming news to pass time, entertain oneself, or out of escapism than when using news to keep up-to-date with politics (H1). Secondly, we hypothesize the extent to which people are confident in their own cognitive abilities to moderate that relationship: When people are overconfident in their own capabilities to estimate the relevance of information, they are more likely to have higher levels of algorithmic appreciation, due to the third person effect (H2). For testing those two pre-registered hypotheses, we conducted an online survey with a sample of 268 US participants and replicated our study using a sample of 384 Dutch participants. The results show that the first hypothesis cannot be supported by our data. However, a positive interaction between overconfidence and algorithmic appreciation for the gratification of surveillance (i.e., gaining information about the world, society, and politics) was found in both samples. Thereby, our study contributes to our understanding of the underlying reasons people have for choosing different forms of gatekeeping when selecting news.
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spelling Epistemic Overconfidence in Algorithmic News Selectionalgorithmic appreciation; algorithmic gatekeepers; algorithmic news selection; third person effect; uses and gratificationsThe process of news consumption has undergone great changes over the past decade: Information is now available in an ever-increasing amount from a plethora of sources. Recent work suggests that most people would favor algorithmic solutions over human editors. This stands in contrast to public and scholarly debate about the pitfalls of algorithmic news selection—i.e., the so-called “filter bubbles.” This study therefore investigates reasons and motivations which might lead people to prefer algorithmic gatekeepers over human ones. We expect that people have more algorithmic appreciation when consuming news to pass time, entertain oneself, or out of escapism than when using news to keep up-to-date with politics (H1). Secondly, we hypothesize the extent to which people are confident in their own cognitive abilities to moderate that relationship: When people are overconfident in their own capabilities to estimate the relevance of information, they are more likely to have higher levels of algorithmic appreciation, due to the third person effect (H2). For testing those two pre-registered hypotheses, we conducted an online survey with a sample of 268 US participants and replicated our study using a sample of 384 Dutch participants. The results show that the first hypothesis cannot be supported by our data. However, a positive interaction between overconfidence and algorithmic appreciation for the gratification of surveillance (i.e., gaining information about the world, society, and politics) was found in both samples. Thereby, our study contributes to our understanding of the underlying reasons people have for choosing different forms of gatekeeping when selecting news.Cogitatio2021-11-18info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.17645/mac.v9i4.4167oai:ojs.cogitatiopress.com:article/4167Media and Communication; Vol 9, No 4 (2021): Algorithmic Systems in the Digital Society; 182-1972183-2439reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://www.cogitatiopress.com/mediaandcommunication/article/view/4167https://doi.org/10.17645/mac.v9i4.4167https://www.cogitatiopress.com/mediaandcommunication/article/view/4167/4167https://www.cogitatiopress.com/mediaandcommunication/article/downloadSuppFile/4167/1519Copyright (c) 2021 Mariken van der Velden, Felicia Loecherbachhttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessvan der Velden, MarikenLoecherbach, Felicia2022-12-20T10:57:32Zoai:ojs.cogitatiopress.com:article/4167Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:20:17.766657Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Epistemic Overconfidence in Algorithmic News Selection
title Epistemic Overconfidence in Algorithmic News Selection
spellingShingle Epistemic Overconfidence in Algorithmic News Selection
van der Velden, Mariken
algorithmic appreciation; algorithmic gatekeepers; algorithmic news selection; third person effect; uses and gratifications
title_short Epistemic Overconfidence in Algorithmic News Selection
title_full Epistemic Overconfidence in Algorithmic News Selection
title_fullStr Epistemic Overconfidence in Algorithmic News Selection
title_full_unstemmed Epistemic Overconfidence in Algorithmic News Selection
title_sort Epistemic Overconfidence in Algorithmic News Selection
author van der Velden, Mariken
author_facet van der Velden, Mariken
Loecherbach, Felicia
author_role author
author2 Loecherbach, Felicia
author2_role author
dc.contributor.author.fl_str_mv van der Velden, Mariken
Loecherbach, Felicia
dc.subject.por.fl_str_mv algorithmic appreciation; algorithmic gatekeepers; algorithmic news selection; third person effect; uses and gratifications
topic algorithmic appreciation; algorithmic gatekeepers; algorithmic news selection; third person effect; uses and gratifications
description The process of news consumption has undergone great changes over the past decade: Information is now available in an ever-increasing amount from a plethora of sources. Recent work suggests that most people would favor algorithmic solutions over human editors. This stands in contrast to public and scholarly debate about the pitfalls of algorithmic news selection—i.e., the so-called “filter bubbles.” This study therefore investigates reasons and motivations which might lead people to prefer algorithmic gatekeepers over human ones. We expect that people have more algorithmic appreciation when consuming news to pass time, entertain oneself, or out of escapism than when using news to keep up-to-date with politics (H1). Secondly, we hypothesize the extent to which people are confident in their own cognitive abilities to moderate that relationship: When people are overconfident in their own capabilities to estimate the relevance of information, they are more likely to have higher levels of algorithmic appreciation, due to the third person effect (H2). For testing those two pre-registered hypotheses, we conducted an online survey with a sample of 268 US participants and replicated our study using a sample of 384 Dutch participants. The results show that the first hypothesis cannot be supported by our data. However, a positive interaction between overconfidence and algorithmic appreciation for the gratification of surveillance (i.e., gaining information about the world, society, and politics) was found in both samples. Thereby, our study contributes to our understanding of the underlying reasons people have for choosing different forms of gatekeeping when selecting news.
publishDate 2021
dc.date.none.fl_str_mv 2021-11-18
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.17645/mac.v9i4.4167
oai:ojs.cogitatiopress.com:article/4167
url https://doi.org/10.17645/mac.v9i4.4167
identifier_str_mv oai:ojs.cogitatiopress.com:article/4167
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.cogitatiopress.com/mediaandcommunication/article/view/4167
https://doi.org/10.17645/mac.v9i4.4167
https://www.cogitatiopress.com/mediaandcommunication/article/view/4167/4167
https://www.cogitatiopress.com/mediaandcommunication/article/downloadSuppFile/4167/1519
dc.rights.driver.fl_str_mv Copyright (c) 2021 Mariken van der Velden, Felicia Loecherbach
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Mariken van der Velden, Felicia Loecherbach
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Cogitatio
publisher.none.fl_str_mv Cogitatio
dc.source.none.fl_str_mv Media and Communication; Vol 9, No 4 (2021): Algorithmic Systems in the Digital Society; 182-197
2183-2439
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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