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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 401–450 of 490 papers

TitleStatusHype
State of the Art Models for Fake News Detection TasksCode1
A Deep Learning Approach for Automatic Detection of Fake NewsCode0
Credulous Users and Fake News: a Real Case Study on the Propagation in Twitter—0
Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection—0
French Tweet Corpus for Automatic Stance Detection—0
Measuring the Impact of Readability Features in Fake News Detection—0
Data Augmentation using Machine Translation for Fake News Detection in the Urdu Language—0
CLFD: A Novel Vectorization Technique and Its Application in Fake News Detection—0
Annotating and Analyzing Biased Sentences in News Articles using Crowdsourcing—0
GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social MediaCode1
Adaptive Interaction Fusion Networks for Fake News Detection—0
BanFakeNews: A Dataset for Detecting Fake News in BanglaCode1
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News—0
Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social Networks—0
SAFE: Similarity-Aware Multi-Modal Fake News DetectionCode1
Fake News Detection with Different Models—0
Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention—0
Fake News Detection by means of Uncertainty Weighted Causal GraphsCode0
Detecting Fake News with Capsule Neural Networks—0
Two-path Deep Semi-supervised Learning for Timely Fake News Detection—0
Improving Generalizability of Fake News Detection Methods using Propensity Score MatchingCode1
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data RepositoryCode1
To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers—0
Stance Detection Benchmark: How Robust Is Your Stance Detection?Code1
Weak Supervision for Fake News Detection via Reinforcement LearningCode0
A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements—0
r/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News DetectionCode0
Credibility-based Fake News Detection—0
Veritas Annotator: Discovering the Origin of a Rumour—0
Detecting Fake News with Weak Social Supervision—0
Localization of Fake News Detection via Multitask Transfer LearningCode0
SCG: Spotting Coordinated Groups in Social Media—0
Learning from Fact-checkers: Analysis and Generation of Fact-checking LanguageCode0
Fake news detection using Deep LearningCode0
LEX-GAN: Layered Explainable Rumor Detector Based on Generative Adversarial Networks—0
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection—0
Machine Learning Approach to Fact-Checking in West Slavic Languages—0
The Limitations of Stylometry for Detecting Machine-Generated Fake News—0
Exploiting Multi-domain Visual Information for Fake News Detection—0
Tensor Factorization with Label Information for Fake News DetectionCode0
Gradual Argumentation Evaluation for Stance Aggregation in Automated Fake News Detection—0
Fake News Detection as Natural Language InferenceCode0
BREAKING! Presenting Fake News Corpus for Automated Fact Checking—0
Fake News Detection using Stance Classification: A Survey—0
Deep Two-path Semi-supervised Learning for Fake News DetectionCode0
Orwellian-times at SemEval-2019 Task 4: A Stylistic and Content-based Classifier—0
Vernon-fenwick at SemEval-2019 Task 4: Hyperpartisan News Detection using Lexical and Semantic Features—0
Fake News Detection using Deep Markov Random Fields—0
Defending Against Neural Fake NewsCode0
A Benchmark Study of Machine Learning Models for Online Fake News DetectionCode0
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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