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

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Showing 201–250 of 490 papers

TitleStatusHype
User Modeling and User Profiling: A Comprehensive Survey—0
LOSS-GAT: Label Propagation and One-Class Semi-Supervised Graph Attention Network for Fake News Detection—0
An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Models—0
Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection—0
Fact-checking based fake news detection: a review—0
Exploring news intent and its application: A theory-driven approachCode0
Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It—0
A Revisit of Fake News Dataset with Augmented Fact-checking by ChatGPT—0
Fuzzy Deep Hybrid Network for Fake News DetectionCode0
Can Out-of-Domain data help to Learn Domain-Specific Prompts for Multimodal Misinformation Detection?Code0
ExFake: Towards an Explainable Fake News Detection Based on Content and Social Context Information—0
BanMANI: A Dataset to Identify Manipulated Social Media News in BanglaCode0
Emotion Detection for Misinformation: A Review—0
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation—0
COVIDFakeExplainer: An Explainable Machine Learning based Web Application for Detecting COVID-19 Fake News—0
Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting—0
GRaMuFeN: Graph-based Multi-modal Fake News Detection in Social Media—0
fakenewsbr: A Fake News Detection Platform for Brazilian Portuguese—0
Machine Learning Technique Based Fake News Detection—0
Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Model—0
Debunking Disinformation: Revolutionizing Truth with NLP in Fake News Detection—0
Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts—0
Performance Analysis of Transformer Based Models (BERT, ALBERT and RoBERTa) in Fake News DetectionCode0
How Good Are SOTA Fake News Detectors—0
Argument Attribution Explanations in Quantitative Bipolar Argumentation Frameworks (Technical Report)—0
Fake News Detection Through Graph-based Neural Networks: A Survey—0
X-CapsNet For Fake News Detection—0
Findings of Factify 2: Multimodal Fake News Detection—0
Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language ModelsCode0
Emulating Reader Behaviors for Fake News Detection—0
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake NewsCode0
See How You Read? Multi-Reading Habits Fusion Reasoning for Multi-modal Fake News DetectionCode0
FakeSwarm: Improving Fake News Detection with Swarming Characteristics—0
Improving Generalization for Multimodal Fake News DetectionCode0
Fake News Detection Through Temporally Evolving User InteractionsCode0
Fake News Detection and Behavioral Analysis: Case of COVID-19—0
Editable Graph Neural Network for Node Classifications—0
Unsupervised Domain-agnostic Fake News Detection using Multi-modal Weak Signals—0
aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert OpinionsCode0
Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasing—0
It's All in the Embedding! Fake News Detection Using Document EmbeddingsCode0
MisRoBÆRTa: Transformers versus MisinformationCode0
Interpretable Detection of Out-of-Context Misinformation with Neural-Symbolic-Enhanced Large Multimodal Model—0
Similarity-Aware Multimodal Prompt Learning for Fake News Detection—0
Multi-modal Fake News Detection on Social Media via Multi-grained Information Fusion—0
Classifying COVID-19 Related Tweets for Fake News Detection and Sentiment Analysis with BERT-based Models—0
No Place to Hide: Dual Deep Interaction Channel Network for Fake News Detection based on Data Augmentation—0
FNR: a similarity and transformer-based approach to detect multi-modal fake news in social mediaCode0
A New cross-domain strategy based XAI models for fake news detection—0
Exploring Semantic Perturbations on GroverCode0
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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