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 26–50 of 98 papers

TitleStatusHype
Evaluating BERT-based Pre-training Language Models for Detecting Misinformation—0
Vital Node Identification in Complex Networks Using a Machine Learning-Based Approach—0
DUCK: Rumour Detection on Social Media by Modelling User and Comment Propagation Networks—0
Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification—0
A Survey on Stance Detection for Mis- and Disinformation Identification—0
MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related MicroblogsCode0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and CountermeasuresCode0
PESTO: A Post-User Fusion Network for Rumour Detection on Social Media—0
Personalized multi-faceted trust modeling to determine trust links in social media and its potential for misinformation management—0
What goes on inside rumour and non-rumour tweets and their reactions: A Psycholinguistic Analyses—0
Rumour Detection via Zero-shot Cross-lingual Transfer Learning—0
Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language—0
BERT based classification system for detecting rumours on Twitter—0
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter—0
A Survey on Stance Detection for Mis- and Disinformation Identification—0
COVID-19 Misinformation on Twitter: Multilingual Analysis—0
Revisiting Rumour Stance Classification: Dealing with Imbalanced Data—0
A Deep Content-Based Model for Persian Rumor Verification—0
A semi-supervised model for Persian rumor verification based on content information—0
“A Little Birdie Told Me ... ” - Inductive Biases for Rumour Stance Detection on Social Media—0
Measuring What Counts: The case of Rumour Stance Classification—0
QMUL-SDS at CheckThat! 2020: Determining COVID-19 Tweet Check-Worthiness Using an Enhanced CT-BERT with Numeric Expressions—0
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity—0
COVID-19 and Arabic Twitter: How can Arab World Governments and Public Health Organizations Learn from Social Media?—0
A Model to Measure the Spread Power of Rumors—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