mlsanityData to 7 Oct 2026

Predicting Factuality of Reporting and Bias of News Media Sources

arXiv 1810.01765 ↗First posted 2 Oct 2018cs.IR cs.LG stat.MLcited by 71

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Abstract (arXiv)

We present a study on predicting the factuality of reporting and bias of news media. While previous work has focused on studying the veracity of claims or documents, here we are interested in characterizing entire news media. These are under-studied but arguably important research problems, both in their own right and as a prior for fact-checking systems. We experiment with a large list of news websites and with a rich set of features derived from (i) a sample of articles from the target news medium, (ii) its Wikipedia page, (iii) its Twitter account, (iv) the structure of its URL, and (v) information about the Web traffic it attracts. The experimental results show sizable performance gains over the baselines, and confirm the importance of each feature type.

Key facts. Cited by 71 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Oct 2018.

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Citing papers per year: 2021: 19; 2022: 12; 2023: 13; 2024: 12; 2025: 9; 2026: 6.

71 papers.

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  1. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,919
  2. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  3. 2023Can Large Language Models Transform Computational Social Science?cited by 245
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  5. 2023Factuality Challenges in the Era of Large Language Modelscited by 125
  6. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  7. 2022Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selectioncited by 52
  8. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  9. 2025Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checkingcited by 29
  10. 2021A Survey on Predicting the Factuality and the Bias of News Mediacited by 20
  11. 2022Infusing Knowledge from Wikipedia to Enhance Stance Detectioncited by 20
  12. 2024Retrieval-Augmented Generation with Estimation of Source Reliabilitycited by 19
38 more
  1. 2023LAraBench: Benchmarking Arabic AI with Large Language Modelscited by 16
  2. 2025Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMscited by 16
  3. 2023Adapting Fake News Detection to the Era of Large Language Modelscited by 14
  4. 2021To Protect and To Serve? Analyzing Entity-Centric Framing of Police Violencecited by 12
  5. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  6. 2022Discord Questions: A Computational Approach To Diversity Analysis in News Coveragecited by 11
  7. 2024Generating Media Background Checks for Automated Source Critical Reasoningcited by 10
  8. 2024Reliability Estimation of News Media Sources: Birds of a Feather Flock Togethercited by 7
  9. 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Languagecited by 6
  10. 2022GREENER: Graph Neural Networks for News Media Profilingcited by 6
  11. 2023Predicting Sentence-Level Factuality of News and Bias of Media Outletscited by 6
  12. 2024VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoningcited by 6
  13. 2021Hidden Biases in Unreliable News Detection Datasetscited by 5
  14. 2022Modeling Multi-level Context for Informational Bias Detection by Contrastive Learning and Sentential Graph Networkcited by 5
  15. 2022Identifying and Characterizing Active Citizens who Refute Misinformation in Social Mediacited by 5
  16. 2021Capturing Stance Dynamics in Social Media: Open Challenges and Research Directionscited by 4
  17. 2023An Interactive Framework for Profiling News Media Sourcescited by 4
  18. 2023Instances and Labels: Hierarchy-aware Joint Supervised Contrastive Learning for Hierarchical Multi-Label Text Classificationcited by 4
  19. 2023"We Demand Justice!": Towards Social Context Grounding of Political Textscited by 4
  20. 2024Fake News Detection: It's All in the Data!cited by 4
  21. 2025Attacks by Content: Automated Fact-checking is an AI Security Issuecited by 4
  22. 2022Interpretable Fake News Detection with Topic and Deep Variational Modelscited by 3
  23. 2023Unsupervised Domain-agnostic Fake News Detection using Multi-modal Weak Signalscited by 3
  24. 2023Interactively Learning Social Media Representations Improves News Source Factuality Detectioncited by 3
  25. 2024Sentence-level Media Bias Analysis with Event Relation Graphcited by 3
  26. 2024Yesterday's News: Benchmarking Multi-Dimensional Out-of-Distribution Generalization of Misinformation Detection Modelscited by 3
  27. 2025Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Expertscited by 3
  28. 2021Deception detection in text and its relation to the cultural dimension of individualism/collectivismcited by 2
  29. 2021Predicting the Factuality of Reporting of News Media Using Observations About User Attention in Their YouTube Channelscited by 2
  30. 2023Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Termcited by 2
  31. 2024Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitationscited by 2
  32. 2024Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactionscited by 2
  33. 2024MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Mediacited by 2
  34. 2025Multi-document Summarization through Multi-document Event Relation Graph Reasoning in LLMs: a case study in Framing Bias Mitigationcited by 2
  35. 2021Claim Verification using a Multi-GAN based Modelcited by 1
  36. 2021FR-Detect: A Multi-Modal Framework for Early Fake News Detection on Social Media Using Publishers Featurescited by 1
  37. 2021A Machine Learning Pipeline to Examine Political Bias with Congressional Speechescited by 1
  38. 2022Evons: A Dataset for Fake and Real News Virality Analysis and Predictioncited by 1

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