Sarcasm Detection

The goal of Sarcasm Detection is to determine whether a sentence is sarcastic or non-sarcastic. Sarcasm is a type of phenomenon with specific perlocutionary effects on the hearer, such as to break their pattern of expectation. Consequently, correct understanding of sarcasm often requires a deep understanding of multiple sources of information, including the utterance, the conversational context, and, frequently some real world facts.

Source: Attentional Multi-Reading Sarcasm Detection

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 126–150 of 266 papers

Title	Date	Tasks	Status	Hype
An Investigation into the Contribution of Locally Aggregated Descriptors to Figurative Language Identification	Nov 1, 2021	Language IdentificationNatural Language Understanding	CodeCode Available	0
Multimodal Learning using Optimal Transport for Sarcasm and Humor Detection	Oct 21, 2021	Humor DetectionSarcasm Detection	—Unverified	0
Perceived and Intended Sarcasm Detection with Graph Attention Networks	Oct 8, 2021	Graph AttentionSarcasm Detection	CodeCode Available	1
AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset	Oct 5, 2021	ArticlesSarcasm Detection	—Unverified	0
Multi-Modal Sarcasm Detection Based on Contrastive Attention Mechanism	Sep 30, 2021	Sarcasm Detection	CodeCode Available	1
Does Commonsense help in detecting Sarcasm?	Sep 17, 2021	Language ModelingLanguage Modelling	CodeCode Available	0
A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict	Sep 8, 2021	Sarcasm DetectionSentence	CodeCode Available	0
Sarcasm Detection and Building an English Language Corpus in Real Time	Sep 1, 2021	Sarcasm Detection	—Unverified	0
Sarcasm Detection in Twitter -- Performance Impact while using Data Augmentation: Word Embeddings	Aug 23, 2021	Data AugmentationOpinion Mining	CodeCode Available	0
FiLMing Multimodal Sarcasm Detection with Attention	Aug 9, 2021	Opinion MiningSarcasm Detection	CodeCode Available	0
sarcasm detection and quantification in arabic tweets	Aug 3, 2021	Binary ClassificationSarcasm Detection	—Unverified	0
Sarcasm Detection: A Comparative Study	Jul 5, 2021	Sarcasm DetectionSentiment Analysis	—Unverified	0
Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language	Jun 23, 2021	Arabic Sentiment AnalysisMulti-Task Learning	—Unverified	0
Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literature	Jun 10, 2021	Cultural Vocal Bursts Intensity PredictionSarcasm Detection	—Unverified	0
¡Qué maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline	Jun 1, 2021	Sarcasm Detection	—Unverified	0
Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations	May 20, 2021	ClassificationMulti-modal Classification	CodeCode Available	1
!Qué maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline	May 12, 2021	Sarcasm Detection	—Unverified	0
Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection	Apr 19, 2021	Meta-LearningSarcasm Detection	CodeCode Available	0
Zero-Resource Multi-Dialectal Arabic Natural Language Understanding	Apr 14, 2021	named-entity-recognitionNamed Entity Recognition	—Unverified	0
Explainable Detection of Sarcasm in Social Media	Apr 1, 2021	Sarcasm Detection	—Unverified	0
SarcasmDet at Sarcasm Detection Task 2021 in Arabic using AraBERT Pretrained Model	Apr 1, 2021	Sarcasm Detection	—Unverified	0
A Contextual Word Embedding for Arabic Sarcasm Detection with Random Forests	Apr 1, 2021	Data AugmentationSarcasm Detection	—Unverified	0
Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in Arabic	Apr 1, 2021	Sarcasm DetectionSentiment Analysis	CodeCode Available	1
Multi-task Learning Using a Combination of Contextualised and Static Word Embeddings for Arabic Sarcasm Detection and Sentiment Analysis	Apr 1, 2021	Multi-Task LearningNatural Language Understanding	—Unverified	0
Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features	Apr 1, 2021	Sarcasm Detection	—Unverified	0

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All datasets BIG-bench (SNARKS)FigLang 2020 Reddit Dataset FigLang 2020 Twitter Dataset SARC (all-bal)SARC (pol-bal)iSarcasm MUStARD SARC (pol-unbal)WITS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PaLM 2(few-shot, k=3, CoT)	Accuracy	84.8	—	Unverified
2	PaLM 2 (few-shot, k=3, Direct)	Accuracy	78.7	—	Unverified
3	PaLM 540B (few-shot, k=3)	Accuracy	78.1	—	Unverified
4	BLOOM 176B (few-shot, k=3)	Accuracy	72.47	—	Unverified
5	Bloomberg GPT (few-shot, k=3)	Accuracy	69.66	—	Unverified
6	GPT-NeoX (few-shot, k=3)	Accuracy	62.36	—	Unverified
7	Chinchilla-70B (few-shot, k=5)	Accuracy	58.6	—	Unverified
8	Gopher-280B (few-shot, k=5)	Accuracy	48.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT+Aspect-based approaches	F1	0.74	—	Unverified
2	RoBERTa_large - (Separated Context-Response)	F1	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa_large (Context-Response)	F1	0.77	—	Unverified
2	BERT	F1	0.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CASCADE	Accuracy	77	—	Unverified
2	Bag-of-Bigrams	Accuracy	75.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Bag-of-Bigrams	Accuracy	76.5	—	Unverified
2	CASCADE	Accuracy	74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa + Mutation Data Augmentation	F1-Score	0.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MUStARD++	Precision	70.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Bag-of-Words	Avg F1	27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BART	R1	36.88	—	Unverified