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 51–60 of 98 papers

TitleStatusHype
Personalized multi-faceted trust modeling to determine trust links in social media and its potential for misinformation management—0
PESTO: A Post-User Fusion Network for Rumour Detection on Social Media—0
Point Process Modelling of Rumour Dynamics in Social Media—0
Processing and Normalizing Hashtags—0
QMUL-SDS at CheckThat! 2020: Determining COVID-19 Tweet Check-Worthiness Using an Enhanced CT-BERT with Numeric Expressions—0
Reddit Temporal N-gram Corpus and its Applications on Paraphrase and Semantic Similarity in Social Media using a Topic-based Latent Semantic Analysis—0
Revisiting Rumour Stance Classification: Dealing with Imbalanced Data—0
Rumour Detection and Analysis on Twitter—0
Rumour detection using graph neural network and oversampling in benchmark Twitter dataset—0
Rumour Detection via Zero-shot Cross-lingual Transfer Learning—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