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Fake News Detection

Fake News Detection is a natural language processing task that involves identifying and classifying news articles or other types of text as real or fake. The goal of fake news detection is to develop algorithms that can automatically identify and flag fake news articles, which can be used to combat misinformation and promote the dissemination of accurate information.

Papers

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Showing 51–100 of 490 papers

TitleStatusHype
A Generalized Deep Markov Random Fields Framework for Fake News Detection.Code1
A Python Tool for Reconstructing Full News Text from GDELTCode1
A Heuristic-driven Ensemble Framework for COVID-19 Fake News DetectionCode1
AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection DatasetCode1
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data RepositoryCode1
COVID-19 Fake News Detection Using Bidirectional Encoder Representations from Transformers Based ModelsCode1
3HAN: A Deep Neural Network for Fake News DetectionCode1
Fake news detection: Taxonomy and comparative studyCode1
Fake News Detection with Heterogeneous TransformerCode1
FineFake: A Knowledge-Enriched Dataset for Fine-Grained Multi-Domain Fake News DetectionCode1
Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style AttacksCode1
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data GenerationCode1
A Survey on Interpretable Cross-modal ReasoningCode1
Cross-Modal Augmentation for Few-Shot Multimodal Fake News DetectionCode1
Exploring Summarization to Enhance Headline Stance DetectionCode1
Compare to The Knowledge: Graph Neural Fake News Detection with External KnowledgeCode1
AMPLE: Emotion-Aware Multimodal Fusion Prompt Learning for Fake News DetectionCode1
Cross-lingual COVID-19 Fake News DetectionCode1
Cross-lingual Evidence Improves Monolingual Fake News DetectionCode1
GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social MediaCode1
Cross-modal Contrastive Learning for Multimodal Fake News DetectionCode1
Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News DetectionCode1
DAAD: Dynamic Analysis and Adaptive Discriminator for Fake News DetectionCode1
Graph Neural Networks with Continual Learning for Fake News Detection from Social MediaCode1
GAMC: An Unsupervised Method for Fake News Detection using Graph Autoencoder with MaskingCode1
Improving Generalizability of Fake News Detection Methods using Propensity Score MatchingCode1
Automatic Fake News Detection: Are Models Learning to Reason?Code1
Graph-based Modeling of Online Communities for Fake News DetectionCode1
Adapting Fake News Detection to the Era of Large Language ModelsCode1
Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News DetectionCode1
``Liar, Liar Pants on Fire'': A New Benchmark Dataset for Fake News DetectionCode1
LTCR: Long-Text Chinese Rumor Detection DatasetCode1
An Enhanced Fake News Detection System With Fuzzy Deep LearningCode1
Each Fake News is Fake in its Own Way: An Attribution Multi-Granularity Benchmark for Multimodal Fake News DetectionCode1
Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural NetworksCode1
Dual-Teacher De-biasing Distillation Framework for Multi-domain Fake News DetectionCode1
Early Detection of Fake News by Utilizing the Credibility of News, Publishers, and Users Based on Weakly Supervised LearningCode1
Multimodal Fusion with BERT and Attention Mechanism for Fake News DetectionCode1
Enhancing Fake News Detection in Social Media via Label Propagation on Cross-modal Tweet GraphCode1
No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet DetectionCode1
Evaluation of Fake News Detection with Knowledge-Enhanced Language ModelsCode1
Entity-Aware Dual Co-Attention Network for Fake News DetectionCode1
Stance Detection Benchmark: How Robust Is Your Stance Detection?Code1
A Stylometric Inquiry into Hyperpartisan and Fake NewsCode0
FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural NetworkCode0
Fake News Detection via NLP is Vulnerable to Adversarial AttacksCode0
Fake News Detection Through Temporally Evolving User InteractionsCode0
Fake news detection using Deep LearningCode0
FANG-COVID: A New Large-Scale Benchmark Dataset for Fake News Detection in GermanCode0
Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated DataCode0
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All datasetsFNC-1RAWFCGrover-MegaLIARHostility Detection Dataset in HindiCOVID-19 Fake News DatasetMediaEval2016PolitiFactSocial mediaWeibo NER

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Sepúlveda-Torres R., Vicente M., Saquete E., Lloret E., Palomar M. (2021)Weighted Accuracy90.73—Unverified
2ZAINAB A. JAWAD, AHMED J. OBAID (CNN and DNN with SCM, 2022)Weighted Accuracy84.6—Unverified
3Bhatt et al.Weighted Accuracy83.08—Unverified
4Bi-LSTM (max-pooling, attention)Weighted Accuracy82.23—Unverified
53rd place at FNC-1 - Team UCL Machine Reading (Riedel et al., 2017)Weighted Accuracy81.72—Unverified
6Neural method from Mohtarami et al. + TF-IDF (Mohtarami et al., 2018)Weighted Accuracy81.23—Unverified
7Neural method from Mohtarami et al. (Mohtarami et al., 2018)Weighted Accuracy78.97—Unverified
8Baseline based on skip-thought embeddings (Bhatt et al., 2017)Weighted Accuracy76.18—Unverified
9Baseline based on word2vec + hand-crafted features (Bhatt et al., 2017)Weighted Accuracy72.78—Unverified
10Neural baseline based on bi-directional LSTMs (Bhatt et al., 2017)Weighted Accuracy63.11—Unverified
#ModelMetricClaimedVerifiedStatus
1Persuasive Writing StrategyF155.8—Unverified
2HiSSF153.9—Unverified
3CofCEDF151.1—Unverified
4ReActF149.8—Unverified
5Standard prompting with articlesF147.9—Unverified
6CoTF144.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Text-Transformers + Five-fold five model cross-validation +Pseudo Label AlgorithmUnpaired Accuracy98.5—Unverified
2Grover-MegaUnpaired Accuracy92—Unverified
3Grover-LargeUnpaired Accuracy80.8—Unverified
4BERT-LargeUnpaired Accuracy73.1—Unverified
5GPT2 (355M)Unpaired Accuracy70.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Hybrid CNNs (Text + All)Test Accuracy0.27—Unverified
2CNNsTest Accuracy0.27—Unverified
3Hybrid CNNs (Text + Speaker)Test Accuracy0.25—Unverified
4Bi-LSTMsTest Accuracy0.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Auxiliary IndicBertF1 score0.77—Unverified
2Auxiliary IndicBertF1 score0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Ensemble Model + Heuristic Post-ProcessingF10.99—Unverified
#ModelMetricClaimedVerifiedStatus
1SEMI-FNDAccuracy85.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Convolutional Tsetlin Machine1:1 Accuracy91.21—Unverified
#ModelMetricClaimedVerifiedStatus
1TextRNNAccuracy92.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SEMI-FNDAccuracy86.83—Unverified