How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility

30 October 2017

A. Chaney

Brandon M Stewart

Barbara E. Engelhardt

CML

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Papers citing "How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility"

34 / 34 papers shown

Title
User and Recommender Behavior Over Time: Contextualizing Activity, Effectiveness, Diversity, and Fairness in Book Recommendation Samira Vaez Barenji Sushobhan Parajuli Michael D. Ekstrand MLAU 47 0 0 07 May 2025
User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems Jianling Wang Yifan Liu Yinghao Sun Xuejian Ma Yueqi Wang ... Onkar Dalal Ed Chi Lichan Hong Ningren Han Haokai Lu 26 0 0 07 Apr 2025
AdaF^2M^2: Comprehensive Learning and Responsive Leveraging Features in Recommendation System Yongchun Zhu Jingwu Chen Ling Chen Y. Li Feng Zhang Xiao Yang Zuotao Liu 44 0 0 28 Jan 2025
Designing Long-term Group Fair Policies in Dynamical Systems Miriam Rateike Isabel Valera Patrick Forré 28 4 0 21 Nov 2023
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces Omer Nahum Gali Noti David C. Parkes Nir Rosenfeld 16 2 0 18 Jun 2023
Simulating News Recommendation Ecosystem for Fun and Profit Guangping Zhang Dongsheng Li Hansu Gu T. Lu Li Shang Ning Gu 16 0 0 23 May 2023
A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems Nicolò Pagan Joachim Baumann Ezzat Elokda Giulia De Pasquale S. Bolognani Anikó Hannák 27 23 0 10 May 2023
Runtime Monitoring of Dynamic Fairness Properties T. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik 27 14 0 08 May 2023
Causal Inference out of Control: Estimating the Steerability of Consumption Gary Cheng Moritz Hardt Celestine Mendler-Dünner CML 29 1 0 10 Feb 2023
Performative Recommendation: Diversifying Content via Strategic Incentives Itay Eilat Nir Rosenfeld 35 7 0 08 Feb 2023
Recommender Systems: A Primer P. Castells Dietmar Jannach OffRL 26 5 0 06 Feb 2023
Individual Fairness for Social Media Influencers Ş. Ionescu Nicolò Pagan Anikó Hannák FaML 19 2 0 19 Jan 2023
Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems Zhengbang Zhu Rongjun Qin Junjie Huang Xinyi Dai Yang Yu Yong Yu Weinan Zhang 33 2 0 11 Oct 2022
iFlipper: Label Flipping for Individual Fairness Hantian Zhang Ki Hyun Tae Jaeyoung Park Xu Chu Steven Euijong Whang 27 6 0 15 Sep 2022
Hidden Author Bias in Book Recommendation Savvina Daniil Mirjam Cuper Cynthia C. S. Liem Jacco van Ossenbruggen L. Hollink 26 3 0 01 Sep 2022
Performative Reinforcement Learning Debmalya Mandal Stelios Triantafyllou Goran Radanović 25 17 0 30 Jun 2022
Preference Dynamics Under Personalized Recommendations Sarah Dean Jamie Morgenstern 67 34 0 25 May 2022
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation Angelina Wang V. V. Ramaswamy Olga Russakovsky FaML 21 92 0 10 May 2022
Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations A. A. Kocherzhenko Nirmal Sobha Kartha Tengfei Li Hsin-Yi Shih Shih Marco Mandic Mike Fuller Arshak Navruzyan 26 0 0 31 Jan 2022
Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness Nicola Neophytou Bhaskar Mitra Catherine Stinson CML 15 24 0 15 Oct 2021
Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation Michael D. Ekstrand 16 2 0 02 Oct 2021
Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation G. Adomavicius Dietmar Jannach Stephan Leitner Jingjing Zhang 13 8 0 25 Aug 2021
T-RECS: A Simulation Tool to Study the Societal Impact of Recommender Systems Eli Lucherini Matthew Sun Amy A. Winecoff Arvind Narayanan 29 23 0 19 Jul 2021
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems M. Mansoury Himan Abdollahpouri Mykola Pechenizkiy B. Mobasher Robin Burke FaML 13 44 0 07 Jul 2021
Productivity, Portability, Performance: Data-Centric Python Yiheng Wang Yao Zhang Yanzhang Wang Yan Wan Jiao Wang Zhongyuan Wu Yuhao Yang Bowen She 49 94 0 01 Jul 2021
Correcting Exposure Bias for Link Recommendation Shantanu Gupta Hao Wang Zachary Chase Lipton Bernie Wang CML 17 34 0 13 Jun 2021
Addressing the Long-term Impact of ML Decisions via Policy Regret David Lindner Hoda Heidari Andreas Krause OffRL 20 7 0 02 Jun 2021
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning Chao Du Zhifeng Gao Shuo Yuan Lining Gao Z. Li Yifan Zeng Xiaoqiang Zhu Jian Xu Kun Gai Kuang-chih Lee 19 18 0 25 Nov 2020
Theoretical Modeling of the Iterative Properties of User Discovery in a Collaborative Filtering Recommender System Sami Khenissi M. Boujelbene O. Nasraoui 12 23 0 21 Aug 2020
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations Dalin Guo S. Ktena Ferenc Huszár Pranay K. Myana Wenzhe Shi Alykhan Tejani OffRL 17 39 0 03 Aug 2020
Quantifying the Effects of Recommendation Systems Sunshine Chong A. Abeliuk CML 6 5 0 04 Feb 2020
Fairness in Learning-Based Sequential Decision Algorithms: A Survey Xueru Zhang M. Liu FaML 35 51 0 14 Jan 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 305 4,203 0 23 Aug 2019
Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems Bashir Rastegarpanah Krishna P. Gummadi M. Crovella 8 119 0 02 Dec 2018