End-to-end hierarchical approach for emotion detection in short texts

Hadjiharalambous, G., Beisert, K. and Jose, J. M. (2022) End-to-end hierarchical approach for emotion detection in short texts. In: Mathew, J., Santhosh Kumar, G., Deepak, P. and Jose, J. M. (eds.) Responsible Data Science: Select Proceedings of ICDSE 2021. Series: Lecture notes in electrical engineering (940). Springer: Singapore, pp. 1-12. ISBN 9789811944529 (doi: 10.1007/978-981-19-4453-6_1)

Abstract

Textual emotion analysis aims to identify and recognize a set of predefined emotions from the text (e.g., sentences, documents). Vast amounts of textual data are created and distributed daily, for example, in news reports and social media, especially microblogging services. Understanding emotion in short text snippets has become an important area of study due to its proliferation in daily life. This paper proposes a novel hierarchical approach for detecting emotion from short texts (microblogs) and conducts a broad set of experiments. Based on the observation that sentiment classification can get up to 80–90% accuracy, we develop a hierarchical end-to-end emotion classifier in which the first layer is the polarity detector and the second layer is the emotion detector. The proposed hierarchical approach can incorporate state-of-the-art neural models, and we have experimented with a BiLTSM-based self-attention model, a BiGRU model, and a BERT-based model for hierarchical emotion classification. Our approaches are evaluated on four large datasets, demonstrating statistically significant improvements.

• Item Type: Book Sections
• Status: Published
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon
• Authors: Hadjiharalambous, G., Beisert, K., and Jose, J. M.
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: Springer
• ISBN: 9789811944529
• Published Online: 15 November 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Responsible Data Science: Select Proceedings of ICDSE 2021: 1-12
• Publisher Policy: Reproduced in accordance with the publisher copyright policy