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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 51–60 of 343 papers

Title	Date	Tasks	Status	Hype	Score
Hashtag-Guided Low-Resource Tweet Classification	Feb 20, 2023	ClassificationSentiment Analysis	CodeCode Available	0	5
InfoPattern: Unveiling Information Propagation Patterns in Social Media	Nov 27, 2023	Red TeamingStance Detection	CodeCode Available	0	5
Emotion-aware Dual Cross-Attentive Neural Network with Label Fusion for Stance Detection in Misinformative Social Media Content	May 27, 2025	Metric LearningMisinformation	CodeCode Available	0	5
EcoVerse: An Annotated Twitter Dataset for Eco-Relevance Classification, Environmental Impact Analysis, and Stance Detection	Apr 8, 2024	Sentiment AnalysisStance Detection	CodeCode Available	0	5
EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection	Mar 23, 2024	Data AugmentationDecoder	CodeCode Available	0	5
How would Stance Detection Techniques Evolve after the Launch of ChatGPT?	Dec 30, 2022	Language ModellingStance Detection	CodeCode Available	0	5
Human Rationales as Attribution Priors for Explainable Stance Detection	Nov 1, 2021	Stance Detection	CodeCode Available	0	5
Identification of Multimodal Stance Towards Frames of Communication	Dec 1, 2023	Stance Detection	CodeCode Available	0	5
A Retrospective Analysis of the Fake News Challenge Stance-Detection Task	Aug 1, 2018	General ClassificationStance Classification	CodeCode Available	0	5
Legislator Representation Learning with Social Context and Expert Knowledge	Aug 9, 2021	Representation LearningStance Detection	CodeCode Available	0	5

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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