Complex Emotional Intelligence Learning Using Deep Neural Networks (Student Abstract)

Authors

  • Belainine Billal University of Quebec in Montreal
  • Fatiha Sadat University of Quebec in Montreal
  • Hakim Lounis University of Quebec in Montreal

DOI:

https://doi.org/10.1609/aaai.v34i10.7149

Abstract

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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Published

2020-04-03

How to Cite

Billal, B., Sadat, F., & Lounis, H. (2020). Complex Emotional Intelligence Learning Using Deep Neural Networks (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 34(10), 13755-13756. https://doi.org/10.1609/aaai.v34i10.7149

Issue

Section

Student Abstract Track