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Digital Nudging with Recommender Systems: Survey and Future Directions
v1v2 (latest)

Digital Nudging with Recommender Systems: Survey and Future Directions

6 November 2020
Mathias Jesse
Dietmar Jannach
ArXiv (abs)PDFHTML

Papers citing "Digital Nudging with Recommender Systems: Survey and Future Directions"

13 / 13 papers shown
Ads that Stick: Near-Optimal Ad Optimization through Psychological Behavior Models
Ads that Stick: Near-Optimal Ad Optimization through Psychological Behavior Models
Kailash Gopal Darmasubramanian
Akash Pareek
Arindam Khan
Arpit Agarwal
117
0
0
24 Sep 2025
Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline Evaluation
Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline EvaluationACM Conference on Recommender Systems (RecSys), 2025
Pedro R. Pires
Gregório F. Azevedo
Pietro L. Campos
Rafael T. Sereicikas
Tiago A. Almeida
OffRL
166
0
0
24 Jul 2025
Reinforce Lifelong Interaction Value of User-Author Pairs for Large-Scale Recommendation Systems
Reinforce Lifelong Interaction Value of User-Author Pairs for Large-Scale Recommendation Systems
Yisha Li
Lexi Gao
Jingxin Liu
Xiang Gao
Xin Li
Haiyang Lu
Liyin Hong
117
0
0
22 Jul 2025
Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that Matters
Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that MattersACM Transactions on Recommender Systems (TRS), 2024
Dietmar Jannach
Alan Said
Marko Tkalčič
Markus Zanker
320
1
0
25 Nov 2024
(De)Noise: Moderating the Inconsistency Between Human Decision-Makers
(De)Noise: Moderating the Inconsistency Between Human Decision-Makers
Nina Grgić-Hlavca
Junaid Ali
Krishna P. Gummadi
Jennifer Wortman Vaughan
216
2
0
15 Jul 2024
Zero-Shot Recommendations with Pre-Trained Large Language Models for
  Multimodal Nudging
Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging
Rachel M. Harrison
Anton Dereventsov
A. Bibin
297
13
0
02 Sep 2023
BHEISR: Nudging from Bias to Balance -- Promoting Belief Harmony by
  Eliminating Ideological Segregation in Knowledge-based Recommendations
BHEISR: Nudging from Bias to Balance -- Promoting Belief Harmony by Eliminating Ideological Segregation in Knowledge-based Recommendations
Mengyan Wang
Yuxuan Hu
Zihan Yuan
Chenting Jiang
Weihua Li
Shiqing Wu
Quan-wei Bai
164
0
0
06 Jul 2023
An Audit Framework for Adopting AI-Nudging on Children
An Audit Framework for Adopting AI-Nudging on Children
M. B. Ganapini
Enrico Panai
MLAU
125
1
0
25 Apr 2023
Algorithmic Assistance with Recommendation-Dependent Preferences
Algorithmic Assistance with Recommendation-Dependent PreferencesACM Conference on Economics and Computation (EC), 2022
Bryce Mclaughlin
Jann Spiess
423
12
0
16 Aug 2022
Towards Psychologically-Grounded Dynamic Preference Models
Towards Psychologically-Grounded Dynamic Preference ModelsACM Conference on Recommender Systems (RecSys), 2022
Mihaela Curmei
Andreas A. Haupt
Dylan Hadfield-Menell
Benjamin Recht
218
21
0
01 Aug 2022
Estimating and Penalizing Induced Preference Shifts in Recommender
  Systems
Estimating and Penalizing Induced Preference Shifts in Recommender SystemsInternational Conference on Machine Learning (ICML), 2022
Micah Carroll
Anca Dragan
Stuart J. Russell
Dylan Hadfield-Menell
OffRL
343
49
0
25 Apr 2022
Designing a Future Worth Wanting: Applying Virtue Ethics to HCI
Designing a Future Worth Wanting: Applying Virtue Ethics to HCI
T. Gorichanaz
82
2
0
05 Apr 2022
Recognising the importance of preference change: A call for a
  coordinated multidisciplinary research effort in the age of AI
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI
Matija Franklin
Hal Ashton
Rebecca Gorman
Stuart Armstrong
AI4TS
241
28
0
20 Mar 2022
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