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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 101–150 of 490 papers

TitleStatusHype
Learning from Fact-checkers: Analysis and Generation of Fact-checking LanguageCode0
CoVLM: Leveraging Consensus from Vision-Language Models for Semi-supervised Multi-modal Fake News DetectionCode0
CovidMis20: COVID-19 Misinformation Detection System on Twitter Tweets using Deep Learning ModelsCode0
Learning Hierarchical Discourse-level Structure for Fake News DetectionCode0
Is it Fake? News Disinformation Detection on South African News WebsitesCode0
Interpretable Fake News Detection with Topic and Deep Variational ModelsCode0
Is Less Really More? Fake News Detection with Limited InformationCode0
Improving Generalization for Multimodal Fake News DetectionCode0
A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News DetectionCode0
Indonesia's Fake News Detection using Transformer NetworkCode0
It's All in the Embedding! Fake News Detection Using Document EmbeddingsCode0
How Vulnerable Are Automatic Fake News Detection Methods to Adversarial Attacks?Code0
Knowledge Graph informed Fake News Classification via Heterogeneous Representation EnsemblesCode0
LaDiff ULMFiT: A Layer Differentiated training approach for ULMFiTCode0
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake NewsCode0
Hybrid Ensemble for Fake News Detection: An attemptCode0
Combating Hostility: Covid-19 Fake News and Hostile Post Detection in Social MediaCode0
aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert OpinionsCode0
Hostility Detection in Hindi leveraging Pre-Trained Language ModelsCode0
IMCI: Integrate Multi-view Contextual Information for Fact Extraction and VerificationCode0
Applying Automatic Text Summarization for Fake News DetectionCode0
Heterogeneous Subgraph Transformer for Fake News DetectionCode0
Adversarial Style Augmentation via Large Language Model for Robust Fake News DetectionCode0
KGAlign: Joint Semantic-Structural Knowledge Encoding for Multimodal Fake News DetectionCode0
DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News DetectionCode0
A Stylometric Inquiry into Hyperpartisan and Fake NewsCode0
Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social NetworksCode0
GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News DetectionCode0
Fuzzy Deep Hybrid Network for Fake News DetectionCode0
Check-It: A Plugin for Detecting and Reducing the Spread of Fake News and Misinformation on the WebCode0
g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News DetectionCode0
Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource LimitationsCode0
FMNV: A Dataset of Media-Published News Videos for Fake News DetectionCode0
FNR: a similarity and transformer-based approach to detect multi-modal fake news in social mediaCode0
FASSILA: A Corpus for Algerian Dialect Fake News Detection and Sentiment AnalysisCode0
From Scarcity to Capability: Empowering Fake News Detection in Low-Resource Languages with LLMsCode0
Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the WebCode0
BanMANI: A Dataset to Identify Manipulated Social Media News in BanglaCode0
Fake News Detection via NLP is Vulnerable to Adversarial AttacksCode0
FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural NetworkCode0
Ax-to-Grind Urdu: Benchmark Dataset for Urdu Fake News DetectionCode0
FANG-COVID: A New Large-Scale Benchmark Dataset for Fake News Detection in GermanCode0
GETAE: Graph information Enhanced deep neural NeTwork ensemble ArchitecturE for fake news detectionCode0
Fake News Detection in Spanish Using Deep Learning TechniquesCode0
Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated DataCode0
Fake News Detection: a comparison between available Deep Learning techniques in vector spaceCode0
Fake News Detection After LLM Laundering: Measurement and ExplanationCode0
Detection of Human and Machine-Authored Fake News in UrduCode0
An Adversarial Benchmark for Fake News Detection ModelsCode0
FakeFlow: Fake News Detection by Modeling the Flow of Affective InformationCode0
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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