Bangla Food Review Sentimental Analysis using Machine Learning

In this modern age, people are dependent on the internet. They prefer to order food online or Food App rather than the restaurant. They are giving various reviews online about the foods. In this project, we aim to build a machine learning model to analyze the sentiment of that reviews. In Bangladesh, internet users are increasing day by day. So we have decided to build the model for the Bangla language. We have found no Bangla dataset for food reviews that we can use for our project. Then we have collected more than one thousand Bangla food reviews from various online platforms like Foodpanda, Hungrynaki, Shohoz food, Pathao food, etc., and labeled them. After some necessary preprocessing, we have extracted various features from cleaned data and used them to train and test for machine learning and deep learning models. We have come to the result that Long Term Short Term (LSTM), a deep learning model giving the best accuracy, that is 90.89%, where we have used word2sequence as feature extraction. Our research contribution will help the food industry by using this model. This model can help them to understand the Bangla food review sentiment.