Sentiment Analysis on Bengali Text using Lexicon Based Approach

Abstract

In this modern era, we daily involve in the internet strongly. We express our opinion about products, services, books, movies, songs, politics, sports, organizations, etc. through the internet in social media, blogs, micro-blogging websites or any media. Public opinion with Bengali text in internet media is increasing very rapidly. Due to a few works in Bengali text sentiment analysis, it has become an important issue of extracting opinions, emotions from Bengali textual data through Sentiment Analysis (SA) for better knowledge extraction. Sentiment Analysis (SA) is effectively used for classifying the opinion expressed in a text according to its polarity (e.g., positive, negative or neutral). This paper represents a lexicon dictionary-based approach for polarity detection of Bengali text data. We compared our proposed model with machine learning classifiers such as Decision Tree (DT), Naive Bayes (NB) and Support Vector Machine (SVM) classifiers and it works as a much better accurate model for Bengali text polarity detection.