SOTAVerified

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 251–300 of 490 papers

TitleStatusHype
DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News DetectionCode0
Linguistic-style-aware Neural Networks for Fake News DetectionCode0
Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social NetworksCode0
AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs—0
FNDaaS: Content-agnostic Detection of Fake News sites—0
Multimodal Matching-aware Co-attention Networks with Mutual Knowledge Distillation for Fake News Detection—0
An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning—0
Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation—0
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning—0
Traceable and Authenticable Image Tagging for Fake News Detection—0
From Fake News to #FakeNews: Mining Direct and Indirect Relationships among Hashtags for Fake News Detection—0
Leveraging Users' Social Network Embeddings for Fake News Detection on Twitter—0
Using Persuasive Writing Strategies to Explain and Detect Health MisinformationCode0
GREENER: Graph Neural Networks for News Media Profiling—0
Combination Of Convolution Neural Networks And Deep Neural Networks For Fake News Detection—0
Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection—0
Uncertainty-aware Propagation Structure Reconstruction for Fake News Detection—0
A Unified Propagation Forest-based Framework for Fake News Detection—0
Concepts and Experiments on Psychoanalysis Driven Computing—0
CovidMis20: COVID-19 Misinformation Detection System on Twitter Tweets using Deep Learning ModelsCode0
Machine Learning-based Automatic Annotation and Detection of COVID-19 Fake News—0
Interpretable Fake News Detection with Topic and Deep Variational ModelsCode0
IMCI: Integrate Multi-view Contextual Information for Fact Extraction and VerificationCode0
Cross-lingual Transfer Learning for Fake News Detector in a Low-Resource LanguageCode0
A Comparative Study on COVID-19 Fake News Detection Using Different Transformer Based Models—0
Modelling Social Context for Fake News Detection: A Graph Neural Network Based Approach—0
Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2020—0
UrduFake@FIRE2020: Shared Track on Fake News Identification in Urdu—0
Towards Smart Fake News Detection Through Explainable AI—0
Better Reasoning Behind Classification Predictions with BERT for Fake News Detection—0
Dynamic graph neural network for fake news detection—0
Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2021—0
UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu—0
Is Multi-Modal Necessarily Better? Robustness Evaluation of Multi-modal Fake News Detection—0
A Proposed Bi-LSTM Method to Fake News Detection—0
Hybrid Ensemble for Fake News Detection: An attemptCode0
Label Noise-Resistant Mean Teaching for Weakly Supervised Fake News Detection—0
A Multi-Policy Framework for Deep Learning-Based Fake News Detection—0
Annotation-Scheme Reconstruction for “Fake News” and Japanese Fake News Dataset—0
ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification—0
Detecting fake news by enhanced text representation with multi-EDU-structure awareness—0
Multimodal Fake News Detection via CLIP-Guided Learning—0
Lifelong Learning Natural Language Processing Approach for Multilingual Data Classification—0
MiDAS: Multi-integrated Domain Adaptive Supervision for Fake News Detection—0
SEMI-FND: Stacked Ensemble Based Multimodal Inference For Faster Fake News Detection—0
Evaluating Generalizability of Fine-Tuned Models for Fake News DetectionCode0
Arabic Fake News Detection Based on Deep Contextualized Embedding Models—0
MM-Claims: A Dataset for Multimodal Claim Detection in Social MediaCode0
Automatic Fake News Detection: Are current models “fact-checking” or“gut-checking”?—0
Detecting COVID-19 Conspiracy Theories with Transformers and TF-IDF—0
Show:102550
← PrevPage 6 of 10Next →
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