Cover Image

Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lesota, Oleg, Geiger, Jonas, Walder, Max, Kowald, Dominik, Schedl, Markus
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations
by: Kowald, Dominik, et al.
Published: (2020)

Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
by: Li, Zihan, et al.
Published: (2026)

The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias
by: Müllner, Peter, et al.
Published: (2024)

Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
by: Müllner, Peter, et al.
Published: (2026)

Transparency, Privacy, and Fairness in Recommender Systems
by: Kowald, Dominik
Published: (2024)

The Importance of Cognitive Biases in the Recommendation Ecosystem
by: Schedl, Markus, et al.
Published: (2024)

Support the Underground: Characteristics of Beyond-Mainstream Music Listeners
by: Kowald, Dominik, et al.
Published: (2021)

Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models
by: Escobedo, Gustavo, et al.
Published: (2024)

Investigating Popularity Bias Amplification in Recommender Systems Employed in the Entertainment Domain
by: Kowald, Dominik
Published: (2025)

Hybrid Personalization Using Declarative and Procedural Memory Modules of the Cognitive Architecture ACT-R
by: Innerebner, Kevin, et al.
Published: (2025)

Music4All A+A: A Multimodal Dataset for Music Information Retrieval Tasks
by: Geiger, Jonas, et al.
Published: (2025)

Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the Digital Archive Monasterium.net
by: Atzenhofer-Baumgartner, Florian, et al.
Published: (2024)

Challenges in Implementing a Recommender System for Historical Research in the Humanities
by: Atzenhofer-Baumgartner, Florian, et al.
Published: (2024)

What Do Humanities Scholars Need? A User Model for Recommendation in Digital Archives
by: Atzenhofer-Baumgartner, Florian, et al.
Published: (2026)

A Multistakeholder Approach to Value-Driven Co-Design of Recommender System Evaluation Metrics in Digital Archives
by: Atzenhofer-Baumgartner, Florian, et al.
Published: (2025)

Music Recommendation with Large Language Models: Challenges, Opportunities, and Evaluation
by: Epure, Elena V., et al.
Published: (2025)

Impacts of Mainstream-Driven Algorithms on Recommendations for Children Across Domains: A Reproducibility Study
by: Ungruh, Robin, et al.
Published: (2025)

Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
by: Melchiorre, Alessandro B., et al.
Published: (2025)

Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
by: Forster, Andrea, et al.
Published: (2025)

Parameter-Efficient Single Collaborative Branch for Recommendation
by: Moscati, Marta, et al.
Published: (2025)

Familiarizing with Music: Discovery Patterns for Different Music Discovery Needs
by: Moscati, Marta, et al.
Published: (2025)

Single-Branch Network Architectures to Close the Modality Gap in Multimodal Recommendation
by: Ganhör, Christian, et al.
Published: (2025)

Unsupervised Graph Embeddings for Session-based Recommendation with Item Features
by: Peintner, Andreas, et al.
Published: (2025)

Fair Agents: Balancing Multistakeholder Alignment in Multi-Agent Personalization Systems
by: Forster, Andrea, et al.
Published: (2026)

Comparative Analysis of Pretrained Audio Representations in Music Recommender Systems
by: Tamm, Yan-Martin, et al.
Published: (2024)

A Universal Sets-level Optimization Framework for Next Set Recommendation
by: Liu, Yuli, et al.
Published: (2024)

Adopting State-of-the-Art Pretrained Audio Representations for Music Recommender Systems
by: Tamm, Yan-Martin, et al.
Published: (2026)

The Diversity Paradox revisited: Systemic Effects of Feedback Loops in Recommender Systems
by: Barlacchi, Gabriele, et al.
Published: (2026)

A Simulation Framework for Studying Systemic Effects of Feedback Loops in Recommender Systems
by: Barlacchi, Gabriele, et al.
Published: (2025)

Enhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive Learning
by: Seshadri, Pavan, et al.
Published: (2024)

Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?
by: Muellner, Peter, et al.
Published: (2025)

Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
by: Escobedo, Gustavo, et al.
Published: (2024)

Echoes in the Loop: Diagnosing Risks in LLM-Powered Recommender Systems under Feedback Loops
by: Park, Donguk, et al.
Published: (2026)

The Feedback Loop Between Recommendation Systems and Reactive Users
by: Mollabagher, Atefeh, et al.
Published: (2025)

De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems
by: Burke, Robin, et al.
Published: (2025)

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation
by: Cai, Shihao, et al.
Published: (2024)

Learning k-Determinantal Point Processes for Personalized Ranking
by: Liu, Yuli, et al.
Published: (2024)

LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops
by: Xu, Chen, et al.
Published: (2023)

Personalized Denoising Implicit Feedback for Robust Recommender System
by: Zhang, Kaike, et al.
Published: (2025)

Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop
by: Zhou, Yuqi, et al.
Published: (2024)