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Rumour Detection

Rumor detection is the task of identifying rumors, i.e. statements whose veracity is not quickly or ever confirmed, in utterances on social media platforms.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 98 papers

TitleStatusHype
Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text ClassificationCode1
PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen DomainsCode1
The Surprising Performance of Simple Baselines for Misinformation DetectionCode1
Estimating predictive uncertainty for rumour verification modelsCode1
Adversary-Aware Rumor DetectionCode1
DUCK: Rumour Detection on Social Media by Modelling User and Comment Propagation NetworksCode1
Claim Check-Worthiness Detection as Positive Unlabelled LearningCode1
No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet DetectionCode1
Learning Reporting Dynamics during Breaking News for Rumour Detection in Social MediaCode1
An Extensible Framework for Verification of Numerical Claims—0
A semi-supervised approach to message stance classification—0
A semi-supervised model for Persian rumor verification based on content information—0
A Speech Act Classifier for Persian Texts and its Application in Identifying Rumors—0
Assessing the Reasoning Abilities of ChatGPT in the Context of Claim Verification—0
A Survey on Stance Detection for Mis- and Disinformation Identification—0
A Survey on Stance Detection for Mis- and Disinformation Identification—0
Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models—0
Automatic and Manual Web Annotations in an Infrastructure to handle Fake News and other Online Media Phenomena—0
BERT based classification system for detecting rumours on Twitter—0
Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification—0
BLCU\_NLP at SemEval-2019 Task 7: An Inference Chain-based GPT Model for Rumour Evaluation—0
Can Rumour Stance Alone Predict Veracity?—0
Classifying Tweet Level Judgements of Rumours in Social Media—0
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter—0
Contrastive Token-level Explanations for Graph-based Rumour Detection—0
COVID-19 and Arabic Twitter: How can Arab World Governments and Public Health Organizations Learn from Social Media?—0
COVID-19 Misinformation on Twitter: Multilingual Analysis—0
Deception Detection in News Reports in the Russian Language: Lexics and Discourse—0
Detecting Rumours with Latency Guarantees using Massive Streaming Data—0
Detection and Resolution of Rumours in Social Media: A Survey—0
Determining the Veracity of Rumours on Twitter—0
DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics—0
DUCK: Rumour Detection on Social Media by Modelling User and Comment Propagation Networks—0
Early Rumour Detection—0
ECNU at SemEval-2017 Task 8: Rumour Evaluation Using Effective Features and Supervised Ensemble Models—0
Emergent: a novel data-set for stance classification—0
Revisiting Rumour Stance Classification: Dealing with Imbalanced Data—0
A Deep Content-Based Model for Persian Rumor Verification—0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures—0
“A Little Birdie Told Me ... ” - Inductive Biases for Rumour Stance Detection on Social Media—0
All-in-one: Multi-task Learning for Rumour Verification—0
A Model to Measure the Spread Power of Rumors—0
An Analytical Emotion Framework of Rumour Threads on Social Media—0
AndrejJan at SemEval-2019 Task 7: A Fusion Approach for Exploring the Key Factors pertaining to Rumour Analysis—0
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning—0
SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours—0
SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions—0
Spotting Rumors via Novelty Detection—0
Stance Classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations—0
Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language—0
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All datasetsSepehr_RumTel011

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ParsBERT+PCapsNet +SA+Title+ AuxiliaryF-Measure0.95—Unverified
2BERT-SAWSF-Measure0.93—Unverified
3Jahanbakhsh-Nagadeh et al.F-Measure0.83—Unverified
4Common context features + Four SA classesF-Measure0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1CMA_R0..5sec1—Unverified