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Convolutional neural network multi-emotion classifiers
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Convolutional neural network multi-emotion classifiers
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Convolutional neural network multi-emotion classifiers
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Journal Article
Convolutional neural network multi-emotion classifiers
2019
Overview
Natural languages are universal and flexible, but cannot exist without ambiguity. Having more than one attitude and meaning in the same phrase context is the main cause for word or phrase ambiguity. Most previous work on emotion analysis has only covered single-label classification and neglected the presence of multiple emotion labels in one instance. This paper presents multi-emotion classification in Twitter based on Convolutional Neural Networks (CNNs). The applied features are emotion lexicons, word embeddings and frequency distribution. The proposed networks performance is evaluated using state-of-the-art classification algorithms, achieving a hamming score range from 0.46 to 0.52 on the challenging SemEval2018 Task E-c.
Publisher
Princess Sumaya University for Technology,Scientific Research Support Fund of Jordan Princess Sumaya University for Technology,Scientific Research Support Fund of Jordan (SRSF) and Princess Sumaya University for Technology (PSUT)
