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Complex Emotional Intelligence Learning Using Deep Neural Networks (Student Abstract)
Author(s) -
Billal Belainine,
Fatiha Sadat,
Hakim Lounis
Publication year - 2020
Publication title -
proceedings of the aaai conference on artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2374-3468
pISSN - 2159-5399
DOI - 10.1609/aaai.v34i10.7149
Subject(s) - computer science , interpretation (philosophy) , artificial intelligence , representation (politics) , natural language processing , deep learning , artificial neural network , deep neural networks , data science , machine learning , politics , political science , law , programming language
Emotion recognition and mining tasks are often limited by the availability of manually annotated data. Several researchers have used emojis and specific hashtags as forms of training and supervision.This research paper proposes a new textual and social corpus, the corpus labeled using basic emotions following Plutchik's theory. Thus, This paper propose a first study for the representation and interpretation of complex emotional interactions, using deep neural networks.

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