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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 51–98 of 98 papers

TitleStatusHype
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
Early Rumour Detection—0
ECNU at SemEval-2017 Task 8: Rumour Evaluation Using Effective Features and Supervised Ensemble Models—0
Emergent: a novel data-set for stance classification—0
Evaluating BERT-based Pre-training Language Models for Detecting Misinformation—0
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity—0
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
NileTMRG at SemEval-2017 Task 8: Determining Rumour and Veracity Support for Rumours on Twitter.—0
PANACEA: An Automated Misinformation Detection System on COVID-19—0
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
Rumour Detection via News Propagation Dynamics and User Representation Learning—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
RumourEval 2019: Determining Rumour Veracity and Support for Rumours—0
SCRum-9: Multilingual Stance Classification over Rumours on Social Media—0
Domain Generalization for Text Classification with Memory-Based Supervised Contrastive LearningCode0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and CountermeasuresCode0
CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against RumorsCode0
Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTMCode0
Danish Stance Classification and Rumour ResolutionCode0
Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation StructureCode0
CMA-R:Causal Mediation Analysis for Explaining Rumour DetectionCode0
Rumor Detection on Twitter with Tree-structured Recursive Neural NetworksCode0
Rumour Evaluation with Very Large Language ModelsCode0
MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related MicroblogsCode0
Back to the Future -- Sequential Alignment of Text RepresentationsCode0
BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional TransformersCode0
Verifying the Robustness of Automatic Credibility AssessmentCode0
Joint Rumour Stance and Veracity PredictionCode0
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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