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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
Studies Towards Language Independent Fake News Detection—0
Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection—0
Synthetic News Generation for Fake News Classification—0
Tackling Fake News Detection by Interactively Learning Representations using Graph Neural Networks—0
Testing the Robustness of a BiLSTM-based Structural Story Classifier—0
Text Classification using Graph Convolutional Networks: A Comprehensive Survey—0
The 2021 Urdu Fake News Detection Task using Supervised Machine Learning and Feature Combinations—0
Have LLMs Reopened the Pandora's Box of AI-Generated Fake News?—0
The Role of User Profile for Fake News Detection—0
The Truth Becomes Clearer Through Debate! Multi-Agent Systems with Large Language Models Unmask Fake News—0
Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection—0
To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers—0
Toward Discourse-Aware Models for Multilingual Fake News Detection—0
Towards Automatic Fake News Detection: Cross-Level Stance Detection in News Articles—0
Towards Knowledge-Grounded Natural Language Understanding and Generation—0
Towards Smart Fake News Detection Through Explainable AI—0
Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social Networks—0
Traceable and Authenticable Image Tagging for Fake News Detection—0
Transferring Structure Knowledge: A New Task to Fake news Detection Towards Cold-Start Propagation—0
Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection—0
Triple Path Enhanced Neural Architecture Search for Multimodal Fake News Detection—0
Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking—0
TT-BLIP: Enhancing Fake News Detection Using BLIP and Tri-Transformer—0
TUDublin team at Constraint@AAAI2021 -- COVID19 Fake News Detection—0
Two-path Deep Semi-supervised Learning for Timely Fake News Detection—0
Uncertainty-aware Propagation Structure Reconstruction for Fake News Detection—0
A Unified Training Process for Fake News Detection based on Fine-Tuned BERT Model—0
UNITE-FND: Reframing Multimodal Fake News Detection through Unimodal Scene Translation—0
Unseen Fake News Detection Through Casual Debiasing—0
Unsupervised Domain-agnostic Fake News Detection using Multi-modal Weak Signals—0
UrduFake@FIRE2020: Shared Track on Fake News Identification in Urdu—0
UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu—0
User Modeling and User Profiling: A Comprehensive Survey—0
VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoning—0
Veritas Annotator: Discovering the Origin of a Rumour—0
Vernon-fenwick at SemEval-2019 Task 4: Hyperpartisan News Detection using Lexical and Semantic Features—0
Vision-Language Models Struggle to Align Entities across Modalities—0
VMID: A Multimodal Fusion LLM Framework for Detecting and Identifying Misinformation of Short Videos—0
Weighted Accuracy Algorithmic Approach In Counteracting Fake News And Disinformation—0
Words are the Window to the Soul: Language-based User Representations for Fake News Detection—0
X-CapsNet For Fake News Detection—0
Fake News Early Detection: An Interdisciplinary Study—0
FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMs—0
Fake News Spreader Detection on Twitter using Character N-Grams. Notebook for PAN at CLEF 2020—0
Fake news stance detection using stacked ensemble of classifiers—0
Fake or Credible? Towards Designing Services to Support Users' Credibility Assessment of News Content—0
FakeSwarm: Improving Fake News Detection with Swarming Characteristics—0
Feature Extraction of Text for Deep Learning Algorithms: Application on Fake News Detection—0
Findings of Factify 2: Multimodal Fake News Detection—0
Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts—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