Abstract:
Sentiment analysis is a way where huge amount of data can be categorized into different
sentiments, emotions, attitudes or opinions. Using sentiment analysis, public views are
collected can be given prediction of the class that the views belong to. So, for deriving
marketing intelligence sentiment analysis can be performed. It is a vast research field in
the NLP sector. Deep learning is part of that machine learning algorithm but it works on
in depth similarly like the working behavior of the human brain. The study shows a deep
learning approach to sentiment analysis using social media’s Bengali dataset. The dataset
is a representation of views of audience of social media’s Bengali contents and is consists
of around 2994 Bengali comments extracted from social media named Facebook and
YouTube posts and videos. Here Positive, Negative and Neutral classes are used to
categorize the Bengali data. Also, Keras tokenizer is used to tokenize the Bengali text and
to convert it into integer sequence and Keras model was used to run the deep learning
algorithms LSTM and Bi-LSTM. And these deep learning approach such as LSTM and
Bi Directional LSTM has been performed on the dataset and Bi Directional LSTM has
the highest accuracy of 72.25%.
