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 41–50 of 458 papers

Title	Date	Tasks	Status	Hype
Learning Arousal-Valence Representation from Categorical Emotion Labels of Speech	Nov 24, 2023	Dimensionality ReductionEmotion Classification	CodeCode Available	1
PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry	Mar 17, 2020	Emotion ClassificationEmotion Recognition	CodeCode Available	1
An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs	Aug 31, 2018	Emotion ClassificationGeneral Classification	—Unverified	0
An Emotional Comfort Framework for Improving User Satisfaction in E-Commerce Customer Service Chatbots	Jun 1, 2021	Answer SelectionEmotion Classification	—Unverified	0
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text	Mar 24, 2025	Continual PretrainingEmotion Classification	—Unverified	0
An Analysis of Annotated Corpora for Emotion Classification in Text	Aug 1, 2018	ClassificationCross-corpus	—Unverified	0
Analysing the Greek Parliament Records with Emotion Classification	May 24, 2022	ClassificationEmotion Classification	—Unverified	0
AffecThor at SemEval-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets	Jun 1, 2018	Emotion ClassificationGeneral Classification	—Unverified	0
A Comprehensive Analysis of Preprocessing for Word Representation Learning in Affective Tasks	Jul 1, 2020	Emotion ClassificationRepresentation Learning	—Unverified	0
An adversarial learning framework for preserving users' anonymity in face-based emotion recognition	Jan 16, 2020	Emotion ClassificationEmotion Recognition	—Unverified	0

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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