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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 61–70 of 98 papers

TitleStatusHype
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
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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