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Bengali Review Analysis for Predicting Popular Cosmetic Brand Using Machine Learning Classifiers
Tapasy Rabeya, Israt Jahan, Mst. Eshita Khatun , Dr. Sheak Rashed Haider Noori, Sharmin Akter,

Nowadays, online platform has become one of the most popular media to express people’s thought of all ages. That made the online platform a precious source for getting almost every kinds of information. As online shopping is rising in no time in recent years, as a result millions of comments are generating every single day. These users generated opinions on social media and different websites has made it easier for the people choosing the right product for them. Hence, sentimental analysis is a sought-after research topic nowadays. Our research paper has portrayed an experimental study on different cosmetics products review. To do so, we have selected ten popular cosmetic brands for analyzing their product review and chosen to analyze Bengali comments or sentences. The main focus of our work was to get out the most popular cosmetic brands among ten chosen brands. We have applied four classification algorithm such as naive Bayes, random forest, decision tree, and support vector machine for analyzing the final outcome and found vaseline and clear are the most popular brands.

"Sentiment analysis Experimental study Opinion mining Cosmetic product review Bengali comment NLP"
Journal or Conference Name
Lecture Notes in Networks and Systems
Publication Year