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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 301–310 of 343 papers

Title	Date	Tasks	Status	Hype
Automatic detection of stance towards vaccination in online discussion forums	Nov 1, 2017	Binary ClassificationSentiment Analysis	—Unverified	0
Cross-lingual Flames Detection in News Discussions	Sep 1, 2017	Sarcasm DetectionSentiment Analysis	—Unverified	0
Towards the Understanding of Gaming Audiences by Modeling Twitch Emotes	Sep 1, 2017	Information RetrievalStance Detection	—Unverified	0
Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus	Sep 1, 2017	Emotion RecognitionGeneral Classification	—Unverified	0
Fake news stance detection using stacked ensemble of classifiers	Sep 1, 2017	ClassificationFake News Detection	—Unverified	0
Unsupervised Detection of Argumentative Units though Topic Modeling Techniques	Sep 1, 2017	Argument MiningOpinion Mining	—Unverified	0
Human Centered NLP with User-Factor Adaptation	Sep 1, 2017	Document ClassificationDomain Adaptation	—Unverified	0
UWaterloo at SemEval-2017 Task 8: Detecting Stance towards Rumours with Topic Independent Features	Aug 1, 2017	Rumour DetectionStance 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
OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields	Aug 1, 2017	Opinion MiningSentiment Analysis	—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