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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 351–400 of 490 papers

TitleStatusHype
Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection—0
FakeFlow: Fake News Detection by Modeling the Flow of Affective InformationCode0
Hostility Detection and Covid-19 Fake News Detection in Social Media—0
ECOL: Early Detection of COVID Lies Using Content, Prior Knowledge and Source InformationCode0
Hostility Detection in Hindi leveraging Pre-Trained Language ModelsCode0
Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection—0
TUDublin team at Constraint@AAAI2021 -- COVID19 Fake News Detection—0
LaDiff ULMFiT: A Layer Differentiated training approach for ULMFiTCode0
Fake News Detection System using XLNet model with Topic Distributions: CONSTRAINT@AAAI2021 Shared Task—0
Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task—0
Model Generalization on COVID-19 Fake News Detection—0
Evaluating Deep Learning Approaches for Covid19 Fake News Detection—0
Identification of COVID-19 related Fake News via Neural Stacking—0
A Heuristic-driven Ensemble Framework for COVID-19 Fake News DetectionCode1
Combating Hostility: Covid-19 Fake News and Hostile Post Detection in Social MediaCode0
Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in EnglishCode1
Transformer based Automatic COVID-19 Fake News Detection SystemCode0
Advanced Machine Learning Techniques for Fake News (Online Disinformation) Detection: A Systematic Mapping Study—0
Fake News Data Collection and Classification: Iterative Query Selection for Opaque Search Engines with Pseudo Relevance Feedback—0
g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News DetectionCode0
An Event Correlation Filtering Method for Fake News Detection—0
Early Detection of Fake News by Utilizing the Credibility of News, Publishers, and Users Based on Weakly Supervised LearningCode1
Fake news detection for the Russian language—0
A Language-Based Approach to Fake News Detection Through Interpretable Features and BRNN—0
Claim extraction from text using transfer learning.—0
ReINTEL Challenge 2020: Vietnamese Fake News Detection usingEnsemble Model with PhoBERT embeddings—0
Fake News Detection in Social Media using Graph Neural Networks and NLP Techniques: A COVID-19 Use-case—0
Two Stage Transformer Model for COVID-19 Fake News Detection and Fact CheckingCode0
Words are the Window to the Soul: Language-based User Representations for Fake News Detection—0
Machine Generation and Detection of Arabic Manipulated and Fake NewsCode0
Lexicon generation for detecting fake news—0
No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet DetectionCode1
Feature Extraction of Text for Deep Learning Algorithms: Application on Fake News Detection—0
Connecting the Dots Between Fact Verification and Fake News Detection—0
Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake NewsCode1
A Review on Fact Extraction and VerificationCode0
SemSeq4FD: Integrating global semantic relationship and local sequential order to enhance text representation for fake news detectionCode0
Fake News Spreader Detection on Twitter using Character N-Grams. Notebook for PAN at CLEF 2020—0
Similarity Detection Pipeline for Crawling a Topic Related Fake News Corpus—0
Sentimental LIAR: Extended Corpus and Deep Learning Models for Fake Claim ClassificationCode1
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection ModelsCode0
FANG: Leveraging Social Context for Fake News Detection Using Graph RepresentationCode1
SGG: Spinbot, Grammarly and GloVe based Fake News Detection—0
Graph-based Modeling of Online Communities for Fake News DetectionCode1
Weighted Accuracy Algorithmic Approach In Counteracting Fake News And Disinformation—0
Machine Learning Explanations to Prevent Overtrust in Fake News Detection—0
Mono vs Multilingual Transformer-based Models: a Comparison across Several Language TasksCode0
Graph Neural Networks with Continual Learning for Fake News Detection from Social MediaCode1
Fake News Detection via Knowledge-driven Multimodal Graph Convolutional Networks—0
BRENDA: Browser Extension for Fake News Detection—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