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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 141–150 of 343 papers

Title	Date	Tasks	Status	Hype
Human Centered NLP with User-Factor Adaptation	Sep 1, 2017	Document ClassificationDomain Adaptation	—Unverified	0
Human-in-the-Loop Disinformation Detection: Stance, Sentiment, or Something Else?	Nov 9, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Collaborative Knowledge Infusion for Low-resource Stance Detection	Mar 28, 2024	Stance Detection	—Unverified	0
Gradual Argumentation Evaluation for Stance Aggregation in Automated Fake News Detection	Aug 1, 2019	Fake News DetectionStance Detection	—Unverified	0
Active learning for detection of stance components	Dec 1, 2016	Active LearningOpinion Mining	—Unverified	0
IDI@NTNU at SemEval-2016 Task 6: Detecting Stance in Tweets Using Shallow Features and GloVe Vectors for Word Representation	Jun 1, 2016	Sentiment AnalysisStance Detection	—Unverified	0
IIITDWD@TamilNLP-ACL2022: Transformer-based approach to classify abusive content in Dravidian Code-mixed text	May 1, 2022	Stance Detection	—Unverified	0
IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification	Aug 1, 2017	Stance DetectionText Categorization	—Unverified	0
COVIDLies: Detecting COVID-19 Misinformation on Social Media	Dec 1, 2020	MisconceptionsMisinformation	—Unverified	0
SHARP: Unlocking Interactive Hallucination via Stance Transfer in Role-Playing Agents	Nov 12, 2024	General KnowledgeHallucination	—Unverified	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