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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 301–350 of 490 papers

TitleStatusHype
Towards Automatic Fake News Detection: Cross-Level Stance Detection in News Articles—0
Is LLMs Hallucination Usable? LLM-based Negative Reasoning for Fake News Detection—0
Is Multi-Modal Necessarily Better? Robustness Evaluation of Multi-modal Fake News Detection—0
Adaptive Learning of Consistency and Inconsistency Information for Fake News Detection—0
Judgment of Thoughts: Courtroom of the Binary Logical Reasoning in Large Language Models—0
KEN: Knowledge Augmentation and Emotion Guidance Network for Multimodal Fake News Detection—0
Applications of Social Media in Hydroinformatics: A Survey—0
Towards Knowledge-Grounded Natural Language Understanding and Generation—0
Label Noise-Resistant Mean Teaching for Weakly Supervised Fake News Detection—0
Adaptive Interaction Fusion Networks for Fake News Detection—0
Large Language Model Agent for Fake News Detection—0
Large Visual-Language Models Are Also Good Classifiers: A Study of In-Context Multimodal Fake News Detection—0
Towards Smart Fake News Detection Through Explainable AI—0
Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social Networks—0
A Proposed Bi-LSTM Method to Fake News Detection—0
Less is More: Unseen Domain Fake News Detection via Causal Propagation Substructures—0
Approaches for Improving the Performance of Fake News Detection in Bangla: Imbalance Handling and Model Stacking—0
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News—0
Traceable and Authenticable Image Tagging for Fake News Detection—0
Leveraging Selective Prediction for Reliable Image Geolocation—0
Leveraging Users' Social Network Embeddings for Fake News Detection on Twitter—0
LEX-GAN: Layered Explainable Rumor Detector Based on Generative Adversarial Networks—0
Lexicon generation for detecting fake news—0
Annotation-Scheme Reconstruction for “Fake News” and Japanese Fake News Dataset—0
Annotation-Scheme Reconstruction for "Fake News" and Japanese Fake News Dataset—0
Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection—0
Lifelong Learning Natural Language Processing Approach for Multilingual Data Classification—0
LingML: Linguistic-Informed Machine Learning for Enhanced Fake News Detection—0
Transferring Structure Knowledge: A New Task to Fake news Detection Towards Cold-Start Propagation—0
LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection—0
Weighted Accuracy Algorithmic Approach In Counteracting Fake News And Disinformation—0
LOSS-GAT: Label Propagation and One-Class Semi-Supervised Graph Attention Network for Fake News Detection—0
Annotating and Analyzing Biased Sentences in News Articles using Crowdsourcing—0
Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection—0
Machine Learning Approach to Fact-Checking in West Slavic Languages—0
Machine Learning-based Automatic Annotation and Detection of COVID-19 Fake News—0
Machine Learning Explanations to Prevent Overtrust in Fake News Detection—0
Machine Learning Technique Based Fake News Detection—0
Triple Path Enhanced Neural Architecture Search for Multimodal Fake News Detection—0
MCFEND: A Multi-source Benchmark Dataset for Chinese Fake News Detection—0
An exploration of features to improve the generalisability of fake news detection models—0
Measuring the Impact of Readability Features in Fake News Detection—0
A New cross-domain strategy based XAI models for fake news detection—0
Methods of Informational Trends Analytics and Fake News Detection on Twitter—0
MiDAS: Multi-integrated Domain Adaptive Supervision for Fake News Detection—0
An Event Correlation Filtering Method for Fake News Detection—0
Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking—0
TT-BLIP: Enhancing Fake News Detection Using BLIP and Tri-Transformer—0
TUDublin team at Constraint@AAAI2021 -- COVID19 Fake News Detection—0
Mitigation of Diachronic Bias in Fake News Detection Dataset—0
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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