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

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Showing 21–30 of 98 papers

TitleStatusHype
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
A semi-supervised approach to message stance classification—0
All-in-one: Multi-task Learning for Rumour Verification—0
Can Rumour Stance Alone Predict Veracity?—0
Classifying Tweet Level Judgements of Rumours in Social Media—0
A Speech Act Classifier for Persian Texts and its Application in Identifying Rumors—0
A Model to Measure the Spread Power of Rumors—0
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter—0
A Deep Content-Based Model for Persian Rumor Verification—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