A Sentiment Analysis Model of Food Reviews in Bengali Texts Based on Deep Learning techniques

cite contains a Tensorflow implementation for our paper. If you find this code useful in your research, please consider citing:

@inproceedings{junaid2022bangla,
title={Bangla Food Review Sentimental Analysis using Machine Learning},
author={Junaid, Mohd Istiaq Hossain and Hossain, Faisal and Upal, Udyan Saha and Tameem, Anjana and Kashim, Abul and Fahmin, Ahmed},
booktitle={2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)},
pages={0347--0353},
year={2022},
organization={IEEE}
}

This project involves reviewing sentiment classification research and developing a machine learning model for sentiment analysis of food reviews in Bangla. We collect raw reviews data from FOODPANDA. Text preprocessing, feature selection, and machine learning classification are project methodologies in the sentiment analysis model. We'll use various natural language processing (NLP) techniques to preprocess the data, extract necessary features such as word frequency, TF-IDF, Glove and word to sequence, and then experiment with and compare the results using various machine learning models.