Detecting Emotion of Users’ Analyzing Social Media Bengali Comments Using Deep Learning Techniques
Sanzana Karim Lora, Nusrat Jahan, Shahana Alam Antora, Nazmus Sakib · 2020
Bengali is one of the most spoken languages in the world. Nowadays, many people share their thoughts, emotions, and ideas through social media using the Bengali language. Facebook comments are one of the sources of sharing opinions among them. The goal of this study is to classify positive and negative emotions accurately with the help of the Facebook comments dataset. For this work, different deep learning models called Stacked Long short-term memory (LSTM), Stacked LSTM with 1D convolution, CNN with pre-trained word embeddings and, RNN with pre-trained word embedding have been used. The RNN model with pre-trained word embeddings has performed the best among all models with 98.3% accuracy. Other models do not perform well as the RNN model.