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A survey on the impact of AI-based recommenders on human behaviours:
  methodologies, outcomes and future directions

A survey on the impact of AI-based recommenders on human behaviours: methodologies, outcomes and future directions

29 June 2024
Luca Pappalardo
Emanuele Ferragina
Salvatore Citraro
Giuliano Cornacchia
M. Nanni
Giulio Rossetti
Gizem Gezici
F. Giannotti
Margherita Lalli
D. Gambetta
Giovanni Mauro
Virginia Morini
Valentina Pansanella
D. Pedreschi
ArXivPDFHTML

Papers citing "A survey on the impact of AI-based recommenders on human behaviours: methodologies, outcomes and future directions"

4 / 4 papers shown
Title
Model Collapse Demystified: The Case of Regression
Model Collapse Demystified: The Case of Regression
Elvis Dohmatob
Yunzhen Feng
Julia Kempe
26
32
0
12 Feb 2024
An Empirical Investigation of Personalization Factors on TikTok
An Empirical Investigation of Personalization Factors on TikTok
Maximilian Boeker
Aleksandra Urman
MLAU
18
69
0
28 Jan 2022
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
286
4,143
0
23 Aug 2019
How Algorithmic Confounding in Recommendation Systems Increases
  Homogeneity and Decreases Utility
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility
A. Chaney
Brandon M Stewart
Barbara E. Engelhardt
CML
161
312
0
30 Oct 2017
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