Digital nudging with recommender systems: Survey and future directions

Recommender systems are nowadays a pervasive part of our online user experience, where they either serve as information filters or provide us with suggestions for additionally relevant content. These systems thereby influence which information is easily accessible to us and thus affect our decision-...

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Autores principales:	Mathias Jesse, Dietmar Jannach
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Digital nudging Recommender systems Survey Decision making Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
Acceso en línea:	https://doaj.org/article/8b8d206003a44e8a89173b8e78296fd9
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id	oai:doaj.org-article:8b8d206003a44e8a89173b8e78296fd9
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spelling	oai:doaj.org-article:8b8d206003a44e8a89173b8e78296fd92021-12-01T05:03:40ZDigital nudging with recommender systems: Survey and future directions2451-958810.1016/j.chbr.2020.100052https://doaj.org/article/8b8d206003a44e8a89173b8e78296fd92021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S245195882030052Xhttps://doaj.org/toc/2451-9588Recommender systems are nowadays a pervasive part of our online user experience, where they either serve as information filters or provide us with suggestions for additionally relevant content. These systems thereby influence which information is easily accessible to us and thus affect our decision-making processes though the automated selection and ranking of the presented content. Automated recommendations can therefore be seen as digital nudges, because they determine different aspects of the choice architecture for users. In this work, we examine the relationship between digital nudging and recommender systems, topics that so far were mostly investigated in isolation. Through a systematic literature search, we first identified 87 nudging mechanisms, which we categorize in a novel taxonomy. A subsequent analysis then shows that only a small part of these nudging mechanisms was previously investigated in the context of recommender systems. This indicates that there is a huge potential to develop future recommender systems that leverage the power of digital nudging in order to influence the decision-making of users. In this work, we therefore outline potential ways of integrating nudging mechanisms into recommender systems.Mathias JesseDietmar JannachElsevierarticleDigital nudgingRecommender systemsSurveyDecision makingElectronic computers. Computer scienceQA75.5-76.95PsychologyBF1-990ENComputers in Human Behavior Reports, Vol 3, Iss , Pp 100052- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Digital nudging Recommender systems Survey Decision making Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
spellingShingle	Digital nudging Recommender systems Survey Decision making Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990 Mathias Jesse Dietmar Jannach Digital nudging with recommender systems: Survey and future directions
description	Recommender systems are nowadays a pervasive part of our online user experience, where they either serve as information filters or provide us with suggestions for additionally relevant content. These systems thereby influence which information is easily accessible to us and thus affect our decision-making processes though the automated selection and ranking of the presented content. Automated recommendations can therefore be seen as digital nudges, because they determine different aspects of the choice architecture for users. In this work, we examine the relationship between digital nudging and recommender systems, topics that so far were mostly investigated in isolation. Through a systematic literature search, we first identified 87 nudging mechanisms, which we categorize in a novel taxonomy. A subsequent analysis then shows that only a small part of these nudging mechanisms was previously investigated in the context of recommender systems. This indicates that there is a huge potential to develop future recommender systems that leverage the power of digital nudging in order to influence the decision-making of users. In this work, we therefore outline potential ways of integrating nudging mechanisms into recommender systems.
format	article
author	Mathias Jesse Dietmar Jannach
author_facet	Mathias Jesse Dietmar Jannach
author_sort	Mathias Jesse
title	Digital nudging with recommender systems: Survey and future directions
title_short	Digital nudging with recommender systems: Survey and future directions
title_full	Digital nudging with recommender systems: Survey and future directions
title_fullStr	Digital nudging with recommender systems: Survey and future directions
title_full_unstemmed	Digital nudging with recommender systems: Survey and future directions
title_sort	digital nudging with recommender systems: survey and future directions
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/8b8d206003a44e8a89173b8e78296fd9
work_keys_str_mv	AT mathiasjesse digitalnudgingwithrecommendersystemssurveyandfuturedirections AT dietmarjannach digitalnudgingwithrecommendersystemssurveyandfuturedirections
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Digital nudging with recommender systems: Survey and future directions

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