Epistemic Overconfidence in Algorithmic News Selection

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 sc...

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Autores principales:	Mariken van der Velden, Felicia Loecherbach
Formato:	article
Lenguaje:	EN
Publicado:	Cogitatio 2021
Materias:	algorithmic appreciation algorithmic gatekeepers algorithmic news selection third person effect uses and gratifications Communication. Mass media P87-96
Acceso en línea:	https://doaj.org/article/5a7eb47c6756416ab5ace265c38c7d38
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spelling	oai:doaj.org-article:5a7eb47c6756416ab5ace265c38c7d382021-11-18T11:14:12ZEpistemic Overconfidence in Algorithmic News Selection2183-243910.17645/mac.v9i4.4167https://doaj.org/article/5a7eb47c6756416ab5ace265c38c7d382021-11-01T00:00:00Zhttps://www.cogitatiopress.com/mediaandcommunication/article/view/4167https://doaj.org/toc/2183-2439The 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.Mariken van der VeldenFelicia LoecherbachCogitatioarticlealgorithmic appreciationalgorithmic gatekeepersalgorithmic news selectionthird person effectuses and gratificationsCommunication. Mass mediaP87-96ENMedia and Communication, Vol 9, Iss 4, Pp 182-197 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	algorithmic appreciation algorithmic gatekeepers algorithmic news selection third person effect uses and gratifications Communication. Mass media P87-96
spellingShingle	algorithmic appreciation algorithmic gatekeepers algorithmic news selection third person effect uses and gratifications Communication. Mass media P87-96 Mariken van der Velden Felicia Loecherbach Epistemic Overconfidence in Algorithmic News Selection
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.
format	article
author	Mariken van der Velden Felicia Loecherbach
author_facet	Mariken van der Velden Felicia Loecherbach
author_sort	Mariken van der Velden
title	Epistemic Overconfidence in Algorithmic News Selection
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
publisher	Cogitatio
publishDate	2021
url	https://doaj.org/article/5a7eb47c6756416ab5ace265c38c7d38
work_keys_str_mv	AT marikenvandervelden epistemicoverconfidenceinalgorithmicnewsselection AT felicialoecherbach epistemicoverconfidenceinalgorithmicnewsselection
_version_	1718420845311819776

Epistemic Overconfidence in Algorithmic News Selection

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