mlsanityData to 7 Oct 2026

FANG: Leveraging Social Context for Fake News Detection Using Graph Representation

arXiv 2008.07939 ↗First posted 18 Aug 2020cs.SI cs.CL cs.IRcited by 98

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Abstract (arXiv)

We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection. Unlike previous contextual models that have targeted performance, our focus is on representation learning. Compared to transductive models, FANG is scalable in training as it does not have to maintain all nodes, and it is efficient at inference time, without the need to re-process the entire graph. Our experimental results show that FANG is better at capturing the social context into a high fidelity representation, compared to recent graphical and non-graphical models. In particular, FANG yields significant improvements for the task of fake news detection, and it is robust in the case of limited training data. We further demonstrate that the representations learned by FANG generalize to related tasks, such as predicting the factuality of reporting of a news medium.

Key facts. Cited by 98 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Aug 2020.

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Citing papers per year: 2021: 27; 2022: 19; 2023: 25; 2024: 17; 2025: 6; 2026: 4.

98 papers.

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  1. 2021A Comprehensive Survey on Graph Anomaly Detection with Deep Learningcited by 230
  2. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  3. 2021Automated Fact-Checking for Assisting Human Fact-Checkerscited by 144
  4. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  5. 2023Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detectioncited by 69
  6. 2023Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attackscited by 69
  7. 2023Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformationcited by 51
  8. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  9. 2022Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generationcited by 41
  10. 2024DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detectioncited by 41
  11. 2022Generalizing to the Future: Mitigating Entity Bias in Fake News Detectioncited by 38
  12. 2021Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detectioncited by 34
38 more
  1. 2022Zoom Out and Observe: News Environment Perception for Fake News Detectioncited by 34
  2. 2021Towards Fine-Grained Reasoning for Fake News Detectioncited by 32
  3. 2022Memory-Guided Multi-View Multi-Domain Fake News Detectioncited by 31
  4. 2023QACHECK: A Demonstration System for Question-Guided Multi-Hop Fact-Checkingcited by 26
  5. 2021Integrating Pattern- and Fact-based Fake News Detection via Model Preference Learningcited by 25
  6. 2021Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake Newscited by 23
  7. 2023Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphscited by 23
  8. 2021Graph Contrastive Learning for Anomaly Detectioncited by 22
  9. 2021A Survey on Predicting the Factuality and the Bias of News Mediacited by 20
  10. 2022DISARM: Detecting the Victims Targeted by Harmful Memescited by 20
  11. 2023Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detectioncited by 20
  12. 2021Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Documentcited by 19
  13. 2022Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabiccited by 18
  14. 2021The Role of Context in Detecting Previously Fact-Checked Claimscited by 17
  15. 2021Interpretable Propaganda Detection in News Articlescited by 16
  16. 2021Article Reranking by Memory-Enhanced Key Sentence Matching for Detecting Previously Fact-Checked Claimscited by 16
  17. 2022Rumor Detection with Self-supervised Learning on Texts and Social Graphcited by 15
  18. 2022Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challengescited by 15
  19. 2023Adapting Fake News Detection to the Era of Large Language Modelscited by 14
  20. 2021DEAP-FAKED: Knowledge Graph based Approach for Fake News Detectioncited by 13
  21. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  22. 2022Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classificationcited by 11
  23. 2023Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detectioncited by 11
  24. 2023Explore the Potential of LLMs in Misinformation Detection: An Empirical Studycited by 11
  25. 2024A General Black-box Adversarial Attack on Graph-based Fake News Detectorscited by 11
  26. 2025PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformationcited by 11
  27. 2021Unified Dual-view Cognitive Model for Interpretable Claim Verificationcited by 10
  28. 2023Exploiting User Comments for Early Detection of Fake News Prior to Users' Commentingcited by 10
  29. 2021Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotionscited by 9
  30. 2021Adaptive Visibility Graph Neural Network and its Application in Modulation Classificationcited by 9
  31. 2022CrowdChecked: Detecting Previously Fact-Checked Claims in Social Mediacited by 9
  32. 2024Can Large Language Models Detect Rumors on Social Media?cited by 9
  33. 2024Heterogeneous Subgraph Transformer for Fake News Detectioncited by 9
  34. 2021Meta-Path-based Fake News Detection Leveraging Multi-level Social Context Informationcited by 8
  35. 2021Cross-lingual COVID-19 Fake News Detectioncited by 7
  36. 2022Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarkscited by 7
  37. 2023Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasingcited by 7
  38. 2026Robust Fake News Detection using Large Language Models under Adversarial Sentiment Attackscited by 7

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