mlsanityData to 7 Oct 2026

User Preference-aware Fake News Detection

arXiv 2104.12259 ↗First posted 25 Apr 2021cs.SI cs.CLcited by 76

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Abstract (arXiv)

Disinformation and fake news have posed detrimental effects on individuals and society in recent years, attracting broad attention to fake news detection. The majority of existing fake news detection algorithms focus on mining news content and/or the surrounding exogenous context for discovering deceptive signals; while the endogenous preference of a user when he/she decides to spread a piece of fake news or not is ignored. The confirmation bias theory has indicated that a user is more likely to spread a piece of fake news when it confirms his/her existing beliefs/preferences. Users' historical, social engagements such as posts provide rich information about users' preferences toward news and have great potential to advance fake news detection. However, the work on exploring user preference for fake news detection is somewhat limited. Therefore, in this paper, we study the novel problem of exploiting user preference for fake news detection. We propose a new framework, UPFD, which simultaneously captures various signals from user preferences by joint content and graph modeling. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. We release our code and data as a benchmark for GNN-based fake news detection: https://github.com/safe-graph/GNN-FakeNews.

Key facts. Cited by 76 papers in the map (data through 7 Oct 2026). Builds on 22 of its 38 references that are in the map. First posted on arXiv 25 Apr 2021.

Builds on

22 of 38 references.

References · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  3. 2017Inductive Representation Learning on Large Graphscited by 6,284
  4. 2018How Powerful are Graph Neural Networks?cited by 4,355
  5. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  6. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
  7. 2018Hierarchical Graph Representation Learning with Differentiable Poolingcited by 786
  8. 2017"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detectioncited by 361
  9. 2017Fake News Detection on Social Media: A Data Mining Perspectivecited by 334
  10. 2018FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Mediacited by 281
  11. 2019Fake News Detection on Social Media using Geometric Deep Learningcited by 115
  12. 2020GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Mediacited by 108
10 more
  1. 2017CSI: A Hybrid Deep Model for Fake News Detectioncited by 101
  2. 2015A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classificationcited by 92
  3. 2020Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERTcited by 69
  4. 2020Graph Neural Networks with Continual Learning for Fake News Detection from Social Mediacited by 43
  5. 2019Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitationcited by 32
  6. 2018Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detectioncited by 25
  7. 2020Graph-based Modeling of Online Communities for Fake News Detectioncited by 21
  8. 2020Mixup-Transformer: Dynamic Data Augmentation for NLP Taskscited by 15
  9. 2018Studying Fake News via Network Analysis: Detection and Mitigationcited by 14
  10. 2021VoterFraud2020: a Multi-modal Dataset of Election Fraud Claims on Twittercited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 15; 2023: 15; 2024: 25; 2025: 12; 2026: 6.

76 papers.

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  1. 2021A Comprehensive Survey on Graph Anomaly Detection with Deep Learningcited by 230
  2. 2023Can LLM-Generated Misinformation Be Detected?cited by 173
  3. 2022MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Datasetcited by 59
  4. 2024DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detectioncited by 41
  5. 2022Generalizing to the Future: Mitigating Entity Bias in Fake News Detectioncited by 38
  6. 2021Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practicescited by 24
  7. 2022A Survey of Graph-based Deep Learning for Anomaly Detection in Distributed Systemscited by 20
  8. 2023FakeGPT: Fake News Generation, Explanation and Detection of Large Language Modelscited by 16
  9. 2024Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FRONDcited by 16
  10. 2023Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalizationcited by 15
  11. 2023GAMC: An Unsupervised Method for Fake News Detection using Graph Autoencoder with Maskingcited by 14
  12. 2022The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detectioncited by 11
38 more
  1. 2022On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approachcited by 11
  2. 2023Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detectioncited by 11
  3. 2023Explore the Potential of LLMs in Misinformation Detection: An Empirical Studycited by 11
  4. 2024A General Black-box Adversarial Attack on Graph-based Fake News Detectorscited by 11
  5. 2024Safety in Graph Machine Learning: Threats and Safeguardscited by 11
  6. 2024MSynFD: Multi-hop Syntax aware Fake News Detectioncited by 10
  7. 2024On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networkscited by 10
  8. 2024Heterogeneous Subgraph Transformer for Fake News Detectioncited by 9
  9. 2022Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarkscited by 7
  10. 2023SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detectioncited by 7
  11. 2024Multitask Active Learning for Graph Anomaly Detectioncited by 7
  12. 2024Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunitiescited by 7
  13. 2024Distributed-Order Fractional Graph Operating Networkcited by 7
  14. 2022Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issuescited by 6
  15. 2022Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networkscited by 6
  16. 2023State of the Art and Potentialities of Graph-level Learningcited by 6
  17. 2024On the Risk of Evidence Pollution for Malicious Social Text Detection in the Era of LLMscited by 5
  18. 2023DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News Detectioncited by 4
  19. 2022Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social Networkscited by 3
  20. 2023Fake News Detection Through Graph-based Neural Networks: A Surveycited by 3
  21. 2023False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulationscited by 3
  22. 2023GLAD: Content-aware Dynamic Graphs For Log Anomaly Detectioncited by 3
  23. 2024Putting Context in Context: the Impact of Discussion Structure on Text Classificationcited by 3
  24. 2024Faithful Interpretation for Graph Neural Networkscited by 3
  25. 2024Revisiting Fake News Detection: Towards Temporality-aware Evaluation by Leveraging Engagement Earlinesscited by 3
  26. 2022On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processingcited by 2
  27. 2022Exploring Fake News Detection with Heterogeneous Social Media Context Graphscited by 2
  28. 2022AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputscited by 2
  29. 2023Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurementcited by 2
  30. 2023Dual-Teacher De-biasing Distillation Framework for Multi-domain Fake News Detectioncited by 2
  31. 2024A Multimodal Adaptive Graph-based Intelligent Classification Model for Fake Newscited by 2
  32. 2025MPPFND: A Dataset and Analysis of Detecting Fake News with Multi-Platform Propagationcited by 2
  33. 2025A Dynamic Knowledge Update-Driven Model with Large Language Models for Fake News Detectioncited by 2
  34. 2025Conf-Profile: A Confidence-Driven Reasoning Paradigm for Label-Free User Profilingcited by 2
  35. 2022Characterizing Internal Evasion Attacks in Federated Learningcited by 1
  36. 2022Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agendacited by 1
  37. 2023Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Modelscited by 1
  38. 2024The Future of Combating Rumors? Retrieval, Discrimination, and Generationcited by 1

50 most cited of 76 All 76 (JSON)