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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
The Cloud of Knowing: Non-factive al-ta `know' (as a Neg-raiser) in Korean—0
The Rumour Mill: Making the Spread of Misinformation Explicit and Tangible—0
Towards Detecting Rumours in Social Media—0
Using Gaussian Processes for Rumour Stance Classification in Social Media—0
UWaterloo at SemEval-2017 Task 8: Detecting Stance towards Rumours with Topic Independent Features—0
Veritas Annotator: Discovering the Origin of a Rumour—0
Vital Node Identification in Complex Networks Using a Machine Learning-Based Approach—0
What goes on inside rumour and non-rumour tweets and their reactions: A Psycholinguistic Analyses—0
Evaluating BERT-based Pre-training Language Models for Detecting Misinformation—0
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity—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