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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

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Showing 1–50 of 98 papers

TitleStatusHype
Estimating predictive uncertainty for rumour verification modelsCode1
Claim Check-Worthiness Detection as Positive Unlabelled LearningCode1
No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet DetectionCode1
PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen DomainsCode1
Adversary-Aware Rumor DetectionCode1
DUCK: Rumour Detection on Social Media by Modelling User and Comment Propagation NetworksCode1
The Surprising Performance of Simple Baselines for Misinformation DetectionCode1
Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text ClassificationCode1
Learning Reporting Dynamics during Breaking News for Rumour Detection in Social MediaCode1
Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation StructureCode0
Domain Generalization for Text Classification with Memory-Based Supervised Contrastive LearningCode0
Joint Rumour Stance and Veracity PredictionCode0
CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against RumorsCode0
Danish Stance Classification and Rumour ResolutionCode0
Verifying the Robustness of Automatic Credibility AssessmentCode0
CMA-R:Causal Mediation Analysis for Explaining Rumour DetectionCode0
Rumour Evaluation with Very Large Language ModelsCode0
MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related MicroblogsCode0
BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional TransformersCode0
Rumor Detection on Twitter with Tree-structured Recursive Neural NetworksCode0
Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTMCode0
Back to the Future -- Sequential Alignment of Text RepresentationsCode0
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
Evaluating BERT-based Pre-training Language Models for Detecting Misinformation—0
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity—0
From Clickbait to Fake News Detection: An Approach based on Detecting the Stance of Headlines to Articles—0
Handling and Mining Linguistic Variation in UGC—0
Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter—0
IITP at SemEval-2017 Task 8 : A Supervised Approach for Rumour Evaluation—0
Implementing BERT and fine-tuned RobertA to detect AI generated news by ChatGPT—0
Journalist-in-the-Loop: Continuous Learning as a Service for Rumour Analysis—0
Mama Edha at SemEval-2017 Task 8: Stance Classification with CNN and Rules—0
Measuring What Counts: The case of Rumour Stance Classification—0
Model-Agnostic and Diverse Explanations for Streaming Rumour Graphs—0
Modeling Tweet Arrival Times using Log-Gaussian Cox Processes—0
NileTMRG at SemEval-2017 Task 8: Determining Rumour and Veracity Support for Rumours on Twitter.—0
PANACEA: An Automated Misinformation Detection System on COVID-19—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