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 31–40 of 98 papers

TitleStatusHype
A semi-supervised approach to message stance classification—0
All-in-one: Multi-task Learning for Rumour Verification—0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures—0
BLCU\_NLP at SemEval-2019 Task 7: An Inference Chain-based GPT Model for Rumour Evaluation—0
Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification—0
An Extensible Framework for Verification of Numerical Claims—0
BERT based classification system for detecting rumours on Twitter—0
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning—0
“A Little Birdie Told Me ... ” - Inductive Biases for Rumour Stance Detection on Social Media—0
DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics—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