Author, as appears in the article.: Jabreel, Mohammed; Moreno, Antonio
Department: Enginyeria Informàtica i Matemàtiques
e-ISSN: 2076-3417
URV's Author/s: Moreno Ribas, Antonio
Keywords: Twitter Sentiment analysis Opinion mining Emotion classification Deep learning
Abstract: © 2019 by the authors. Currently, people use online social media such as Twitter or Facebook to share their emotions and thoughts. Detecting and analyzing the emotions expressed in social media content benefits many applications in commerce, public health, social welfare, etc. Most previous work on sentiment and emotion analysis has only focused on single-label classification and ignored the co-existence of multiple emotion labels in one instance. This paper describes the development of a novel deep learning-based system that addresses the multiple emotion classification problem in Twitter. We propose a novel method to transform it to a binary classification problem and exploit a deep learning approach to solve the transformed problem. Our system outperforms the state-of-the-art systems, achieving an accuracy score of 0.59 on the challenging SemEval2018 Task 1:E-cmulti-label emotion classification problem.
Thematic Areas: Química Process chemistry and technology Physics, applied Materials science, multidisciplinary Materials science (miscellaneous) Materials science (all) Materiais Instrumentation General materials science General engineering Fluid flow and transfer processes Engineering, multidisciplinary Engineering (miscellaneous) Engineering (all) Engenharias ii Engenharias i Computer science applications Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Chemistry, multidisciplinary Biodiversidade Astronomia / física
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 20763417
Author's mail: antonio.moreno@urv.cat
Author identifier: 0000-0003-3945-2314
Record's date: 2024-10-12
Journal volume: 9
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.mdpi.com/2076-3417/9/6/1123
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Applied Sciences-Basel. 9 (6): 1123-1123
APA: Jabreel, Mohammed; Moreno, Antonio (2019). A deep learning-based approach for multi-label emotion classification in Tweets. Applied Sciences-Basel, 9(6), 1123-1123. DOI: 10.3390/app9061123
Article's DOI: 10.3390/app9061123
Entity: Universitat Rovira i Virgili
Journal publication year: 2019
Publication Type: Journal Publications
Repositori URV