Emotion Classification

Emotion classification, or emotion categorization, is the task of recognising emotions to classify them into the corresponding category. Given an input, classify it as 'neutral or no emotion' or as one, or more, of several given emotions that best represent the mental state of the subject's facial expression, words, and so on. Some example benchmarks include ROCStories, Many Faces of Anger (MFA), and GoEmotions. Models can be evaluated using metrics such as the Concordance Correlation Coefficient (CCC) and the Mean Squared Error (MSE).

Papers

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Showing 381–390 of 458 papers

Title	Date	Tasks	Status
Persian Slang Text Conversion to Formal and Deep Learning of Persian Short Texts on Social Media for Sentiment Classification	Mar 9, 2024	Emotion ClassificationSentiment Analysis	—Unverified
PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and \#hashtags	Jun 1, 2018	BIG-bench Machine LearningEmotion Classification	—Unverified
Podlab at SemEval-2019 Task 3: The Importance of Being Shallow	Jun 1, 2019	ClassificationEmotion Classification	—Unverified
Probabilistic Ensembles of Zero- and Few-Shot Learning Models for Emotion Classification	Sep 1, 2021	Emotion ClassificationFew-Shot Learning	—Unverified
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis	Jun 1, 2018	Emotion ClassificationEmotion Recognition	—Unverified
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel Attention	Oct 20, 2023	Deep LearningEmotion Classification	CodeCode Available
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution Networks	Dec 5, 2019	Dependency ParsingEmotion Classification	CodeCode Available
NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer Learning	Apr 18, 2018	Emotion ClassificationTransfer Learning	CodeCode Available
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNN	Feb 21, 2019	Emotion ClassificationGeneral Classification	CodeCode Available
NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion Analysis	Feb 16, 2023	Emotion ClassificationEmotion Recognition	CodeCode Available

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All datasets CMU-MOSEI SemEval 2018 Task 1E-c EWALK MFA ROCStories ArmanEmo CAER-Dynamic RAVDESS ShortPersianEmo

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MARLIN (ViT-L)	Accuracy	80.63	—	Unverified
2	MARLIN (ViT-B)	Accuracy	80.6	—	Unverified
3	MARLIN (ViT-S)	Accuracy	80.38	—	Unverified
4	ConCluGen	Accuracy	66.48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SpanEmo	Accuracy	0.6	—	Unverified
2	BERT+DK	Accuracy	0.59	—	Unverified
3	BERT-GCN	Accuracy	0.59	—	Unverified
4	Transformer (finetune)	Macro-F1	0.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ProxEmo (ours)	Accuracy	82.4	—	Unverified
2	STEP [bhattacharya2019step]	Accuracy	78.24	—	Unverified
3	Baseline (Vanilla LSTM) [Ewalk]	Accuracy	55.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MLKNN	F-F1 score (Comb.)	0.34	—	Unverified
2	CC - XGB	F-F1 score (Comb.)	0.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Semi-supervision	F1	65.88	—	Unverified
2	NPN + Explanation Training	F1	30.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Deep ParsBERT	Macro F1	0.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CAERNet	Accuracy	77.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ERANN-0-4	Top-1 Accuracy	74.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Deep ParsBERT	Macro F1	0.71	—	Unverified