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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
GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News DetectionCode0
A Self-Learning Multimodal Approach for Fake News Detection—0
Detecting Fake News on Social Media: A Novel Reliability Aware Machine-Crowd Hybrid Intelligence-Based MethodCode0
Graph with Sequence: Broad-Range Semantic Modeling for Fake News Detection—0
GETAE: Graph information Enhanced deep neural NeTwork ensemble ArchitecturE for fake news detectionCode0
Revisiting Fake News Detection: Towards Temporality-aware Evaluation by Leveraging Engagement EarlinessCode1
Strengthening Fake News Detection: Leveraging SVM and Sophisticated Text Vectorization Techniques. Defying BERT?—0
A Regularized LSTM Method for Detecting Fake News Articles—0
VMID: A Multimodal Fusion LLM Framework for Detecting and Identifying Misinformation of Short Videos—0
Less is More: Unseen Domain Fake News Detection via Causal Propagation Substructures—0
A Multimodal Adaptive Graph-based Intelligent Classification Model for Fake News—0
FASSILA: A Corpus for Algerian Dialect Fake News Detection and Sentiment AnalysisCode0
A Survey on Automatic Credibility Assessment of Textual Credibility Signals in the Era of Large Language Models—0
Detection of Human and Machine-Authored Fake News in UrduCode0
Have LLMs Reopened the Pandora's Box of AI-Generated Fake News?—0
Enriching GNNs with Text Contextual Representations for Detecting Disinformation Campaigns on Social MediaCode0
Health Misinformation in Social Networks: A Survey of IT Approaches—0
NexusIndex: Integrating Advanced Vector Indexing and Multi-Model Embeddings for Robust Fake News Detection—0
AMPLE: Emotion-Aware Multimodal Fusion Prompt Learning for Fake News DetectionCode1
Real-time Fake News from Adversarial FeedbackCode0
CrediRAG: Network-Augmented Credibility-Based Retrieval for Misinformation Detection in Reddit—0
MMCFND: Multimodal Multilingual Caption-aware Fake News Detection for Low-resource Indic Languages—0
Text Classification using Graph Convolutional Networks: A Comprehensive Survey—0
VERITAS-NLI : Validation and Extraction of Reliable Information Through Automated Scraping and Natural Language InferenceCode0
CoVLM: Leveraging Consensus from Vision-Language Models for Semi-supervised Multi-modal Fake News DetectionCode0
Overview of Factify5WQA: Fact Verification through 5W Question-Answering—0
Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI—0
Judgment of Thoughts: Courtroom of the Binary Logical Reasoning in Large Language Models—0
LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection—0
DAAD: Dynamic Analysis and Adaptive Discriminator for Fake News DetectionCode1
Adaptive Learning of Consistency and Inconsistency Information for Fake News Detection—0
Official-NV: An LLM-Generated News Video Dataset for Multimodal Fake News Detection—0
A Semi-supervised Fake News Detection using Sentiment Encoding and LSTM with Self-Attention—0
Cross-Modal Augmentation for Few-Shot Multimodal Fake News DetectionCode1
Large Visual-Language Models Are Also Good Classifiers: A Study of In-Context Multimodal Fake News Detection—0
Transferring Structure Knowledge: A New Task to Fake news Detection Towards Cold-Start Propagation—0
Detect, Investigate, Judge and Determine: A Novel LLM-based Framework for Few-shot Fake News Detection—0
Search, Examine and Early-Termination: Fake News Detection with Annotation-Free Evidences—0
Health Misinformation Detection in Web Content via Web2Vec: A Structural-, Content-based, and Context-aware Approach based on Web2Vec—0
Fake News Detection: It's All in the Data!Code5
Fake News Detection and Manipulation Reasoning via Large Vision-Language Models—0
POLygraph: Polish Fake News Dataset—0
An Enhanced Fake News Detection System With Fuzzy Deep LearningCode1
Adversarial Style Augmentation via Large Language Model for Robust Fake News DetectionCode0
COOL: Comprehensive Knowledge Enhanced Prompt Learning for Domain Adaptive Few-shot Fake News Detection—0
Enhancing Fake News Detection in Social Media via Label Propagation on Cross-modal Tweet GraphCode1
VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoning—0
Evaluating the Efficacy of Large Language Models in Detecting Fake News: A Comparative Analysis—0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
Let Silence Speak: Enhancing Fake News Detection with Generated Comments from Large Language ModelsCode1
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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