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 201–225 of 343 papers

Title	Date	Tasks	Status	Hype
tWT--WT: A Dataset to Assert the Role of Target Entities for Detecting Stance of Tweets	Jun 1, 2021	SentenceStance Detection	CodeCode Available	0
Target-Aware Data Augmentation for Stance Detection	Jun 1, 2021	Data AugmentationLanguage Modeling	—Unverified	0
Knowledge Enhanced Masked Language Model for Stance Detection	May 26, 2021	Language ModelingLanguage Modelling	CodeCode Available	1
Stance Detection with BERT Embeddings for Credibility Analysis of Information on Social Media	May 21, 2021	Fake News DetectionMisinformation	—Unverified	0
Adversarial Learning for Zero-Shot Stance Detection on Social Media	May 14, 2021	Stance DetectionZero-Shot Stance Detection	CodeCode Available	1
AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking	Apr 28, 2021	Fact CheckingMisinformation	CodeCode Available	0
Cross-Domain Label-Adaptive Stance Detection	Apr 15, 2021	Domain AdaptationMixture-of-Experts	CodeCode Available	1
Synthetic Examples Improve Cross-Target Generalization: A Study on Stance Detection on a Twitter corpus.	Apr 1, 2021	Stance Detection	—Unverified	0
Adversarial Training for News Stance Detection: Leveraging Signals from a Multi-Genre Corpus.	Apr 1, 2021	ArticlesStance Detection	—Unverified	0
A Few Topical Tweets are Enough for Effective User Stance Detection	Apr 1, 2021	ClusteringStance Detection	—Unverified	0
University of Copenhagen Participation in TREC Health Misinformation Track 2020	Mar 3, 2021	Language ModelingLanguage Modelling	—Unverified	0
Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection	Mar 2, 2021	Stance Detection	—Unverified	0
A Survey on Stance Detection for Mis- and Disinformation Identification	Feb 27, 2021	Fact CheckingMisinformation	—Unverified	0
Semi-automatic Generation of Multilingual Datasets for Stance Detection in Twitter	Jan 28, 2021	Stance Detection	—Unverified	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
COVIDLies: Detecting COVID-19 Misinformation on Social Media	Dec 1, 2020	MisconceptionsMisinformation	—Unverified	0
Evaluating Unsupervised Representation Learning for Detecting Stances of Fake News	Dec 1, 2020	Representation LearningStance Detection	—Unverified	0
QMUL-SDS @ SardiStance: Leveraging Network Interactions to Boost Performance on Stance Detection using Knowledge Graphs	Nov 2, 2020	AvgKnowledge Graphs	—Unverified	0
“A Little Birdie Told Me ... ” - Inductive Biases for Rumour Stance Detection on Social Media	Nov 1, 2020	MisinformationPosition	—Unverified	0
STANDER: An Expert-Annotated Dataset for News Stance Detection and Evidence Retrieval	Nov 1, 2020	ArticlesMulti-Task Learning	CodeCode Available	0
Unsupervised stance detection for arguments from consequences	Nov 1, 2020	Stance Detection	—Unverified	0
On the Reliability and Validity of Detecting Approval of Political Actors in Tweets	Nov 1, 2020	BenchmarkingSentiment Analysis	—Unverified	0
Incorporating Count-Based Features into Pre-Trained Models for Improved Stance Detection	Oct 18, 2020	MisinformationStance Detection	CodeCode Available	0
Unseen Target Stance Detection with Adversarial Domain Generalization	Oct 12, 2020	Domain GeneralizationStance Detection	CodeCode Available	1
Measuring What Counts: The case of Rumour Stance Classification	Oct 9, 2020	ClassificationGeneral Classification	—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