Emotion Classification In Software Engineering Texts: A Comparative Analysis of Pre-trained Transformers Language Models

Emotion recognition in software engineering texts is critical for understanding developer expressions and improving collaboration. This paper presents a comparative analysis of state-of-the-art Pretrained Language Models (PTMs) for fine-grained emotion classification on two benchmark datasets from G...

Full description

Bibliographic Details

Published in:	2024 IEEE/ACM International Workshop on Natural Language-Based Software Engineering (NLBSE) pp. 73 - 80
Main Author:	Imran, Mia Mohammad
Format:	Conference Proceeding
Language:	English
Published:	ACM 20.04.2024
Subjects:	ALBERT Analytical models Benchmark testing BERT CodeBERT DeBERTa Emotion Classification Emotion recognition GraphCodeBERT Large Language Models RoBERTa Software Task analysis Training Transformers
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!