Beyond Exposure Diversity: Debiasing News Consumption With Topic-Locality Calibration and Personalized Preview Nudges
sigir26-010 · Full research paper · Ruixuan Sun, Matthew Zent, Minzhu Zhao, Xinyi Li, Thanmayee Boyapati, Joseph A. Konstan
Popularity Bias and Long-Tail Debias · 50% Bias Mitigation Methods · 50%
Abstract
In this study, we applied the "personalized diversity nudge framework" with the goal of expanding readers' reading coverage in terms of news locality (i.e., domestic and world news). We designed a novel topic-locality dual calibration algorithmic nudge and a large language model-based news personalization presentation nudge, then launched a 5-week real-user study with 120 U.S. news readers on the news recommendation experiment platform POPROX. With interaction logs and survey responses, we found that algorithmic nudges can successfully increase exposure and consumption diversity, while the impact of LLM-based presentation nudges varied. Participant-level topic interest is a strong predictor of individual clicks, while highlighting the relevance of news articles to prior read articles outperforms generic topic-based and no personalization. We also demonstrate that longitudinal exposure to calibrated news may shift readers' reading habits to value a balanced news digest from both domestic and world articles. Our results provide direction for future work on nudging for diverse consumption in news recommendation systems.
Assigned reviewers
| # | Reviewer | Match | Why (closest evidence publications in the taxonomy) | |
|---|---|---|---|---|
| 1 | Yifan Wang 0017 | 65 | 100 Intersectional Two-sided Fairness in Recommendation (2024) Popularity Bias and Long-Tail Debiasing 83 Improving Long-tail User CTR Prediction via Hierarchical Distribution Alignment (2025) Bias Mitigation Methods 75 Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias (2024) Popularity Bias and Debiasing in Recommendation |
|
| 2 | Sunhao Dai | 57 | 88 Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop (2025) Popularity Bias and Long-Tail Debiasing 71 Unifying Bias and Unfairness in Information Retrieval: New Challenges in the LLM Era (2025) Bias Mitigation Methods 71 Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era (2024) Bias Mitigation Methods |
Area chair
| Area chair | Match | |
|---|---|---|
| Xin Xin 0003 | 42 |
Area-chair candidates (4)
| Xin Xin 0003 assigned | 42 | 10 papers | |
| Xiaoxue Zang | 40 | 4 papers | |
| Pengyue Jia | 40 | 10 papers | |
| Yanan Niu | 40 | 15 papers |
Candidates from the panel ranked by match score
| # | Reviewer | Match | Load | Why | |
|---|---|---|---|---|---|
| 1 | Yifan Wang 0017 assigned | 65 | 3 | 100 Intersectional Two-sided Fairness in Recommendation (2024) Popularity Bias and Long-Tail Debiasing 83 Improving Long-tail User CTR Prediction via Hierarchical Distribution Alignment (2025) Bias Mitigation Methods |
|
| 2 | Sunhao Dai assigned | 57 | 3 | 88 Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop (2025) Popularity Bias and Long-Tail Debiasing 71 Unifying Bias and Unfairness in Information Retrieval: New Challenges in the LLM Era (2025) Bias Mitigation Methods |
|
| 3 | Hao Liu 0078 | 55 | 3 | 71 Mitigating Fine-tuning Bias: A Parameter-Efficient Debiasing Framework for Large Language Models (2026) Bias Mitigation Methods 46 Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective (2025) Contrastive and Self-Supervised Sequential Recommendation |
|
| 4 | Yu-An Liu 0028 | 49 | 3 | 67 Robust Neural Information Retrieval: An Adversarial and Out-of-Distribution Perspective (2026) Robustness and Adversarial IR 67 Robust Information Retrieval (2025) Robustness and Adversarial IR |
|
| 5 | Miaomiao Cai 0001 | 49 | 3 | 75 Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias (2024) Popularity Bias and Debiasing in Recommendation 59 Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning (2024) Popularity Bias and Debiasing in Recommendation |
|
| 6 | Seongmin Park 0002 | 48 | 3 | 62 Bilateral Self-unbiased Learning from Biased Implicit Feedback (2022) Popularity Bias and Debiasing in Recommendation 62 Dual Unbiased Recommender Learning for Implicit Feedback (2021) Popularity Bias and Debiasing in Recommendation |
|
| 7 | Jizhi Zhang | 45 | 3 | 71 Item-side Fairness of Large Language Model-based Recommendation System (2024) Preference Alignment and Optimization 62 Popularity-aware Distributionally Robust Optimization for Recommendation System (2023) Popularity Bias and Debiasing in Recommendation |
|
| 8 | Zechun Niu | 45 | 3 | 48 Distributionally Robust Optimization for Unbiased Learning to Rank (2025) Unbiased Learning to Rank 46 Addressing Personalized Bias for Unbiased Learning to Rank (2025) Unbiased Learning to Rank |
|
| 9 | Yuta Saito | 45 | 3 | 71 Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback (2020) Popularity Bias and Long-Tail Debiasing 71 Towards Resolving Propensity Contradiction in Offline Recommender Learning (2022) Popularity Bias and Long-Tail Debiasing |
|
| 10 | Zhengyi Yang 0007 | 44 | 3 | 71 Item-side Fairness of Large Language Model-based Recommendation System (2024) Preference Alignment and Optimization 46 A Generic Learning Framework for Sequential Recommendation with Distribution Shifts (2023) Contrastive and Self-Supervised Sequential Recommendation |
|
| 11 | Chongming Gao | 43 | 3 | 61 Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation (2023) Popularity Bias and Debiasing in Recommendation 47 SPRec: Self-Play to Debias LLM-based Recommendation (2025) Preference Alignment and Optimization |
|
| 12 | Lichan Hong | 43 | 3 | 71 Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN) (2023) Popularity Bias and Long-Tail Debiasing 44 Improving Training Stability for Multitask Ranking Models in Recommender Systems (2023) Recommendation Systems and Evaluation |
|
| 13 | Ed H. Chi COI: co-author | 43 | 3 | 71 Beyond Globally Optimal: Focused Learning for Improved Recommendations (2017) Popularity Bias and Long-Tail Debiasing 42 Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval (2020) Search and Recommendation Integration |
|
| 15 | Yongxin Ni | 42 | 3 | 82 Causality-Inspired Fair Representation Learning for Multimodal Recommendation (2025) Bias Mitigation Methods 43 An Image Dataset for Benchmarking Recommender Systems with Raw Pixels (2024) Recommendation Systems and Evaluation |
|
| 16 | James Caverlee | 42 | 3 | 71 Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests (2021) Popularity Bias and Long-Tail Debiasing 58 Fairness among New Items in Cold Start Recommender Systems (2021) Fairness Metrics and Evaluation |
|
| 17 | Min Hou 0004 | 42 | 3 | 59 Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning (2024) Popularity Bias and Debiasing in Recommendation 51 InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models (2025) Popularity Bias and Debiasing in Recommendation |
|
| 18 | Yang Song 0008 | 41 | 3 | 47 Inverse Learning with Extremely Sparse Feedback for Recommendation (2024) Robustness to Noise and Distribution Shift 43 LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting (2024) Recommendation Systems and Evaluation |
|
| 19 | Yimeng Bai | 41 | 3 | 43 LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting (2024) Recommendation Systems and Evaluation 43 Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework (2023) Recommendation Systems and Evaluation |
|
| 20 | Jin Chen 0008 | 41 | 3 | 47 Dual Test-Time Training for Out-of-Distribution Recommender System (2025) Robustness to Noise and Distribution Shift 46 Cooperative Retriever and Ranker in Deep Recommenders (2023) Recommendation with Search and Ranking |
|
| 21 | Andrew Parry | 41 | 3 | 67 Axiomatic Guidance for Efficient and Controlled Neural Search (2024) Robustness and Adversarial IR 67 Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models (2024) Robustness and Adversarial IR |
|
| 22 | Theresia Veronika Rampisela | 41 | 3 | 41 Relevance-aware Individual Item Fairness Measures for Recommender Systems: Limitations and Usage Guidelines (2026) Fairness Metrics and Evaluation 41 Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study (2025) Fairness Metrics and Evaluation |
|
| 23 | Jieming Zhu | 41 | 3 | 47 Directional Adversarial Training for Recommender Systems (2020) Robustness to Noise and Distribution Shift 43 Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation (2025) Efficiency and Deployment |
|
| 24 | Shuchang Liu 0001 | 40 | 3 | 45 DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems (2025) Preference Alignment and Optimization 44 Comprehensive List Generation for Multi-Generator Reranking (2025) Recommendation with Search and Ranking |
|
| 27 | Lingling Yi | 40 | 3 | 75 Alleviating Video-length Effect for Micro-video Recommendation (2024) Popularity Bias and Debiasing in Recommendation 75 DVR: Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias (2022) Popularity Bias and Debiasing in Recommendation |
|
| 28 | Riwei Lai | 40 | 3 | 47 DAR: Dimension-Adaptive Recommendation with Multi-Granular Noise Control (2025) Robustness to Noise and Distribution Shift 42 Matryoshka Representation Learning for Recommendation with Layer- and Hardness-Adaptive Negative Sampling (2026) Negative Sampling and Loss Functions |
|
| 29 | Bo Chen 0023 | 40 | 3 | 45 Towards efficient and effective unlearning of large language models for recommendation (2025) Efficiency and Deployment 43 A Comprehensive Survey on Automated Machine Learning for Recommendations (2024) Recommendation Systems and Evaluation |
|
| 30 | Xiao Zhang 0034 | 40 | 3 | 46 When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation (2023) Recommendation with Search and Ranking 44 UniSAR: Modeling User Transition Behaviors between Search and Recommendation (2024) Recommendation with Search and Ranking |
|
| 31 | Hyunsik Yoo | 40 | 3 | 73 Ensuring User-side Fairness in Dynamic Recommender Systems (2024) Popularity Bias and Long-Tail Debiasing 47 Generalizable Recommender System During Temporal Popularity Distribution Shifts (2025) Robustness to Noise and Distribution Shift |
|
| 32 | Shijie Wang 0002 | 40 | 3 | 73 Trustworthy Recommender Systems: Foundations and Frontiers (2023) Popularity Bias and Long-Tail Debiasing 71 CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent (2024) Preference Alignment and Optimization |
|
| 33 | Han Li 0005 | 40 | 3 | 44 Comprehensive List Generation for Multi-Generator Reranking (2025) Recommendation with Search and Ranking 43 RecFlow: An Industrial Full Flow Recommendation Dataset (2025) Recommendation Systems and Evaluation |