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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–450 of 490 papers

TitleStatusHype
A Comparative Study on COVID-19 Fake News Detection Using Different Transformer Based Models—0
CrediRAG: Network-Augmented Credibility-Based Retrieval for Misinformation Detection in Reddit—0
Credulous Users and Fake News: a Real Case Study on the Propagation in Twitter—0
CroMe: Multimodal Fake News Detection using Cross-Modal Tri-Transformer and Metric Learning—0
Credibility-based Fake News Detection—0
COVIDFakeExplainer: An Explainable Machine Learning based Web Application for Detecting COVID-19 Fake News—0
ReINTEL Challenge 2020: Exploiting Transfer Learning Models for Reliable Intelligence Identification on Vietnamese Social Network Sites—0
COOL: Comprehensive Knowledge Enhanced Prompt Learning for Domain Adaptive Few-shot Fake News Detection—0
ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification—0
Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task—0
ReINTEL Challenge 2020: Vietnamese Fake News Detection usingEnsemble Model with PhoBERT embeddings—0
Connecting the Dots Between Fact Verification and Fake News Detection—0
UrduFake@FIRE2020: Shared Track on Fake News Identification in Urdu—0
Data Augmentation using Machine Translation for Fake News Detection in the Urdu Language—0
Dataset of Fake News Detection and Fact Verification: A Survey—0
Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors—0
DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection—0
Debunking Disinformation: Revolutionizing Truth with NLP in Fake News Detection—0
UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu—0
Deception Detection in News Reports in the Russian Language: Lexics and Discourse—0
Deconfounded Reasoning for Multimodal Fake News Detection via Causal Intervention—0
A Hybrid Transformer Model for Fake News Detection: Leveraging Bayesian Optimization and Bidirectional Recurrent Unit—0
User Modeling and User Profiling: A Comprehensive Survey—0
Concepts and Experiments on Psychoanalysis Driven Computing—0
Combining Machine Learning with Knowledge Engineering to detect Fake News in Social Networks-a survey—0
Detecting COVID-19 Conspiracy Theories with Transformers and TF-IDF—0
Combination Of Convolution Neural Networks And Deep Neural Networks For Fake News Detection—0
Detecting fake news by enhanced text representation with multi-EDU-structure awareness—0
A Hybrid Attention Framework for Fake News Detection with Large Language Models—0
Detecting Fake News with Capsule Neural Networks—0
Detecting Fake News with Weak Social Supervision—0
Search, Examine and Early-Termination: Fake News Detection with Annotation-Free Evidences—0
Interpretable Detection of Out-of-Context Misinformation with Neural-Symbolic-Enhanced Large Multimodal Model—0
Detect, Investigate, Judge and Determine: A Novel LLM-based Framework for Few-shot Fake News Detection—0
Detection of fake news on CoViD-19 on Web Search Engines—0
A comparative analysis of Graph Neural Networks and commonly used machine learning algorithms on fake news detection—0
Development of Fake News Model using Machine Learning through Natural Language Processing—0
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection—0
Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models—0
SEMI-FND: Stacked Ensemble Based Multimodal Inference For Faster Fake News Detection—0
Domain Adaptive Fake News Detection via Reinforcement Learning—0
Collaborative Evolution: Multi-Round Learning Between Large and Small Language Models for Emergent Fake News Detection—0
Dynamic graph neural network for fake news detection—0
CLFD: A Novel Vectorization Technique and Its Application in Fake News Detection—0
VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoning—0
Classifying COVID-19 Related Tweets for Fake News Detection and Sentiment Analysis with BERT-based Models—0
Adversarial Examples for Natural Language Classification Problems—0
Editable Graph Neural Network for Node Classifications—0
Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Data—0
Emotion Detection for Misinformation: A Review—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