{"total":23,"rows":[{"id":"2404.11457","title":"Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era","created":"2024-04-17","cited_by_count":98,"area":null},{"id":"2306.13723","title":"Human-AI Coevolution","created":"2023-06-23","cited_by_count":27,"area":null},{"id":"2411.00492","title":"Multi-expert Prompting Improves Reliability, Safety, and Usefulness of Large Language Models","created":"2024-11-01","cited_by_count":14,"area":null},{"id":"2109.02941","title":"Countering Online Hate Speech: An NLP Perspective","created":"2021-09-07","cited_by_count":12,"area":null},{"id":"2112.05084","title":"A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation","created":"2021-12-09","cited_by_count":12,"area":null},{"id":"2210.08786","title":"Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls","created":"2022-10-17","cited_by_count":8,"area":null},{"id":"2109.13589","title":"Learning Ideological Embeddings from Information Cascades","created":"2021-09-28","cited_by_count":6,"area":null},{"id":"2102.12799","title":"Cognitive network science for understanding online social cognitions: A brief review","created":"2021-02-25","cited_by_count":5,"area":null},{"id":"2105.14898","title":"Retweet communities reveal the main sources of hate speech","created":"2021-05-31","cited_by_count":5,"area":null},{"id":"2204.02718","title":"Annotation-Scheme Reconstruction for \"Fake News\" and Japanese Fake News Dataset","created":"2022-04-06","cited_by_count":4,"area":null},{"id":"2305.03223","title":"Structural Group Unfairness: Measurement and Mitigation by means of the Effective Resistance","created":"2023-05-05","cited_by_count":4,"area":null},{"id":"2308.12497","title":"False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations","created":"2023-08-24","cited_by_count":3,"area":null},{"id":"2406.17963","title":"Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories","created":"2024-06-25","cited_by_count":3,"area":null},{"id":"2109.09476","title":"Regulating Ruminative Web-browsing Based on the Counterbalance Modeling Approach","created":"2021-09-20","cited_by_count":2,"area":null},{"id":"2405.09543","title":"Algorithmic Fairness: A Tolerance Perspective","created":"2024-04-26","cited_by_count":2,"area":null},{"id":"2201.05334","title":"This Must Be the Place: Predicting Engagement of Online Communities in a Large-scale Distributed Campaign","created":"2022-01-14","cited_by_count":1,"area":null},{"id":"2412.12588","title":"PerSphere: A Comprehensive Framework for Multi-Faceted Perspective Retrieval and Summarization","created":"2024-12-17","cited_by_count":1,"area":null},{"id":"2307.11621","title":"On the Complexity of the Bipartite Polarization Problem: from Neutral to Highly Polarized Discussions","created":"2023-07-21","cited_by_count":0,"area":null},{"id":"2405.05275","title":"SoMeR: Multi-View User Representation Learning for Social Media","created":"2024-05-02","cited_by_count":0,"area":null},{"id":"2507.20614","title":"Before the Outrage: Challenges and Advances in Predicting Online Antisocial Behavior","created":"2025-07-28","cited_by_count":0,"area":null},{"id":"2510.10474","title":"When or What? Understanding Consumer Engagement on Digital Platforms","created":"2025-10-12","cited_by_count":0,"area":null},{"id":"2510.17289","title":"Addressing Antisocial Behavior in Multi-Party Dialogs Through Multimodal Representation Learning","created":"2025-10-20","cited_by_count":0,"area":null},{"id":"2607.00873","title":"How Ethos and Pathos Appeals Resonate in Reader Interpretations of Social Media Messages","created":"2026-07-01","cited_by_count":0,"area":null}],"next_cursor":null}