A Hybrid Framework for Sentiment Analysis from Bangla Texts

Abstract

Sentiment analysis has gained significant interest from multiple perspectives due to the rise of user interactions on social media and the web. It assists people in choosing the best service or product by analyzing the reviews of available options. Due to the current rise in demand, Bangla sentiment analysis has gained popularity throughout the research community. However, almost all Bangla sentiment analysis research has focused on a single approach, which has created a research gap in this domain. Therefore, this paper proposes a hybrid framework to perform sentiment analysis on Bangla texts that combines machine learning and a rule-based approach. This research starts with the machine learning approach and then integrates its intermediate result with the result of a newly proposed rule-based approach to produce the final sentiment of reviews. The experimental analysis states that the proposed hybrid framework outperforms the previous works with an accuracy of 95.54%, which assures its efficacy.