SOTAVerified

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

Showing 8190 of 98 papers

TitleStatusHype
Rumour detection using graph neural network and oversampling in benchmark Twitter dataset0
Rumour Detection via Zero-shot Cross-lingual Transfer Learning0
RumourEval 2019: Determining Rumour Veracity and Support for Rumours0
SCRum-9: Multilingual Stance Classification over Rumours on Social Media0
SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours0
Domain Generalization for Text Classification with Memory-Based Supervised Contrastive LearningCode0
Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation StructureCode0
Danish Stance Classification and Rumour ResolutionCode0
Rumor Detection on Twitter with Tree-structured Recursive Neural NetworksCode0
Rumour Evaluation with Very Large Language ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ParsBERT+PCapsNet +SA+Title+ AuxiliaryF-Measure0.95Unverified
2BERT-SAWSF-Measure0.93Unverified
3Jahanbakhsh-Nagadeh et al.F-Measure0.83Unverified
4Common context features + Four SA classesF-Measure0.79Unverified
#ModelMetricClaimedVerifiedStatus
1CMA_R0..5sec1Unverified