Emotion Detection in Online Social networks: Using Deep Learning Approach
Date
2022-05-30
Journal Title
Journal ISSN
Volume Title
Publisher
Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh
Abstract
Emotion recognition is one of the most difficult jobs in the Natural Language
Processing (NLP) sector since it relies significantly on contextual information and
mixed emotions in a sentence during the emotion detection process. Therefore, we
propose two deep learning approaches CNN and Bi-LSTM, we built these two models
on a dataset that contains six levels of emotions. The two models have proven to give
good accuracy above 90% on this dataset. From that, we have decided to try them out
on thirteen levels of emotions to see if we can still achieve reasonable performance on
a high level of emotions
Description
Supervised by
Ms. Lutfun Nahar Lota,
Asst. Professor,
Department of Computer Science and Engineering(CSE),
Islamic University of Technology (IUT)
Board Bazar, Gazipur-1704, Bangladesh.
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
Keywords
K-NN, CNN, Bi-LSTM, Deep Learning, Naive Bayes, SVM
Citation
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