Automatic Sentence Classification: A Crucial Component of Sentiment Analysis

Sentence analysis is a crucial task in natural language processing that finds applications in various fields, including sentiment analysis. The growing volume of Bangla data on the Internet has drawn significant attention to sentiment analysis. Bangla is the official language of Bangladesh and is also spoken in the eastern part of India. With the massive increase in Bangla documents, classifying sentimental text in Bangla has become a complex task that can be simplified by effectively categorizing various Bangla sentences. Additionally, people encounter difficulties in distinguishing various Bangla sentences. Hence, it is essential to establish a system that can automatically and accurately identify Bangla sentences. To address this issue, we compared various machine learning and deep learning algorithms in Bangla sentence classification. We created a dataset consisting of over 900 sentences, which we used in modelling. Our approach yields a machine learning accuracy of 65.85% and a deep learning accuracy of 98.02% using LSTM. This system can aid in the effective design of sentiment analysis systems in Bangla.