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Article

A Deep Learning-Based Approach for Multi-Label Emotion Classification in Tweets

1
ITAKA Research Group, Universitat Rovira i Virgili, 43007 Tarragona, Spain
2
Department of Computer Science, Hodeidah University, Hodeidah 1821, Yemen
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(6), 1123; https://doi.org/10.3390/app9061123
Received: 15 February 2019 / Revised: 11 March 2019 / Accepted: 12 March 2019 / Published: 17 March 2019
(This article belongs to the Special Issue Sentiment Analysis for Social Media)
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. View Full-Text
Keywords: opinion mining; sentiment analysis; emotion classification; deep learning; Twitter opinion mining; sentiment analysis; emotion classification; deep learning; Twitter
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MDPI and ACS Style

Jabreel, M.; Moreno, A. A Deep Learning-Based Approach for Multi-Label Emotion Classification in Tweets. Appl. Sci. 2019, 9, 1123. https://doi.org/10.3390/app9061123

AMA Style

Jabreel M, Moreno A. A Deep Learning-Based Approach for Multi-Label Emotion Classification in Tweets. Applied Sciences. 2019; 9(6):1123. https://doi.org/10.3390/app9061123

Chicago/Turabian Style

Jabreel, Mohammed; Moreno, Antonio. 2019. "A Deep Learning-Based Approach for Multi-Label Emotion Classification in Tweets" Appl. Sci. 9, no. 6: 1123. https://doi.org/10.3390/app9061123

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