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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 301–350 of 490 papers

TitleStatusHype
COVID-19 Fake News Detection Using Bidirectional Encoder Representations from Transformers Based ModelsCode1
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text GenerationCode1
Fake News Detection: Experiments and Approaches beyond Linguistic Features—0
Integrating Pattern- and Fact-based Fake News Detection via Model Preference LearningCode1
Fake or Credible? Towards Designing Services to Support Users' Credibility Assessment of News Content—0
MMCoVaR: Multimodal COVID-19 Vaccine Focused Data Repository for Fake News Detection and a Baseline Architecture for Classification—0
End-to-end argumentation knowledge graph construction—0
Towards Fine-Grained Reasoning for Fake News DetectionCode1
Meta-Path-based Fake News Detection Leveraging Multi-level Social Context Information—0
FR-Detect: A Multi-Modal Framework for Early Fake News Detection on Social Media Using Publishers Features—0
Toward Discourse-Aware Models for Multilingual Fake News Detection—0
Mitigation of Diachronic Bias in Fake News Detection Dataset—0
NoFake at CheckThat! 2021: Fake News Detection Using BERT—0
Is it Fake? News Disinformation Detection on South African News WebsitesCode0
Fake News and Phishing Detection Using a Machine Learning Trained Expert System—0
Tackling Fake News Detection by Interactively Learning Representations using Graph Neural Networks—0
Automatic Fake News Detection in Political Platforms - A Transformer-based Approach—0
Multimodal Fusion with Co-Attention Networks for Fake News Detection—0
InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection—0
Cross-lingual Evidence Improves Monolingual Fake News DetectionCode1
Compare to The Knowledge: Graph Neural Fake News Detection with External KnowledgeCode1
How Vulnerable Are Automatic Fake News Detection Methods to Adversarial Attacks?Code0
Indonesia's Fake News Detection using Transformer NetworkCode0
DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection—0
Fake News Detection for Portuguese with Deep Learning—0
Multimodal Emergent Fake News Detection via Meta Neural Process Networks—0
Exploring Summarization to Enhance Headline Stance DetectionCode1
Multimodal Detection of Information Disorder from Social Media—0
SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?—0
Stance Detection with BERT Embeddings for Credibility Analysis of Information on Social Media—0
Explainable Tsetlin Machine framework for fake news detection with credibility score assessmentCode0
Automatic Fake News Detection: Are Models Learning to Reason?Code1
AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection DatasetCode1
User Preference-aware Fake News DetectionCode1
Claim Detection in Biomedical Twitter Posts—0
Multimodal Fusion with BERT and Attention Mechanism for Fake News DetectionCode1
The Surprising Performance of Simple Baselines for Misinformation DetectionCode1
A Heuristic-driven Uncertainty based Ensemble Framework for Fake News Detection in Tweets and News ArticlesCode1
Graph-based Fake News Detection using a Summarization Technique—0
Detection of fake news on CoViD-19 on Web Search Engines—0
On the Role of Images for Analyzing Claims in Social MediaCode0
A Survey on Predicting the Factuality and the Bias of News Media—0
Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models—0
Factorization of Fact-Checks for Low Resource Indian Languages—0
ReINTEL Challenge 2020: Exploiting Transfer Learning Models for Reliable Intelligence Identification on Vietnamese Social Network Sites—0
Fake News Detection: a comparison between available Deep Learning techniques in vector spaceCode0
Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News DetectionCode1
Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Data—0
Hierarchical Multi-head Attentive Network for Evidence-aware Fake News DetectionCode1
A transformer based approach for fighting COVID-19 fake news—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