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Stance Detection

Stance detection is the extraction of a subject's reaction to a claim made by a primary actor. It is a core part of a set of approaches to fake news assessment.

Example:

Source: "Apples are the most delicious fruit in existence"
Reply: "Obviously not, because that is a reuben from Katz's"
Stance: deny

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 251–260 of 343 papers

Title	Date	Tasks	Status	Hype
Zero-Shot Stance Detection using Contextual Data Generation with LLMs	May 19, 2024	Fake News DetectionFew-Shot Learning	CodeCode Available	0
Adversarial Learning-based Stance Classifier for COVID-19-related Health Policies	Sep 10, 2022	Stance Detection	CodeCode Available	0
A Multi-task Model for Sentiment Aided Stance Detection of Climate Change Tweets	Nov 7, 2022	Sentiment AnalysisStance Detection	CodeCode Available	0
An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection	Jan 9, 2021	Information RetrievalOptical Character Recognition (OCR)	CodeCode Available	0
AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking	Apr 28, 2021	Fact CheckingMisinformation	CodeCode Available	0
A Retrospective Analysis of the Fake News Challenge Stance-Detection Task	Aug 1, 2018	General ClassificationStance Classification	CodeCode Available	0
A Retrospective Analysis of the Fake News Challenge Stance Detection Task	Jun 13, 2018	General ClassificationStance Classification	CodeCode Available	0
A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking	Oct 29, 2019	BIG-bench Machine LearningFact Checking	CodeCode Available	0
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task	Jul 11, 2017	Fact CheckingMisinformation	CodeCode Available	0
A Tweet Dataset Annotated for Named Entity Recognition and Stance Detection	Jan 15, 2019	named-entity-recognitionNamed Entity Recognition	CodeCode Available	0

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All datasets MGTAB RumourEval FNC-1 ARC (AI2 Reasoning Challenge)argmin Dhoroni emergent iac1 ibmcs mtsd Perspectrum poldeb

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	RGT	Acc	87.8	—	Unverified
2	Simple-HGN	Acc	85.3	—	Unverified
3	GCN	Acc	82.4	—	Unverified
4	GAT	Acc	82.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	66.58	—	Unverified
2	Kochkina et al. 2017	Accuracy	0.78	—	Unverified
3	Bahuleyan and Vechtomova 2017	Accuracy	0.78	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	83.17	—	Unverified
2	Transition Matrix	F1	77.76	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	64.82	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	62.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BanglaBERT-Dhoroni	Accuracy	0.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	82.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	56.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	88.06	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	63.96	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	83.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	52.76	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	COLA+GPT3.5	Average F1	83.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Boosting	F1	0.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	64.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	58.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	78.61	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT	Average F1	66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MUSE + UMAP (Unsupervised)	Avg F1	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MUSE + UMAP (Unsupervised)	Avg F1	0.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	57.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TESTED	F1	70.98	—	Unverified