Scopus Indexed Paper

Paper Details


Title
Sentiment Analysis of Bangla Song Review- A Lexicon Based Backtracking Approach
Abstract
In the last decade, Sentiment analysis is a prospering experimental topic of research as because of a lot of opinionated data accessible on Blogs & social networking sites. It is the reference to the assignment of Natural Language Processing to decide whether text or content contains any subjective information like positive, negative or not. These social media and other online platforms are giving an immense stage to uncover human's gifts in a fast speed, and average citizens can likewise put their feeling through the remarks which emphatically show how they are accepting another potential. In this paper, we have presented a sentimental analysis of Bengali song reviews from a specific YouTube channel to analyse people acceptance rate of a new young star. For detecting the sentiments, we have used a backtracking algorithm, where the heart of this approach is a sentiment lexicon. And the research showed the backtracking algorithm performed more than 70% accuracy to detect actual public sentiment.
Keywords
Sentiment analysis, Motion pictures, Genetic expression, YouTube, Support vector machines, Classification algorithms, Computer science
Authors
Tapasy Rabeya, Narayan Ranjan Chakraborty, Sanjida Ferdous, Manoranjan Dash, Ahmed Al Marouf
Phone
Journal or Conference Name
Proceedings of 2019 3rd IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2019
Publish Year
2019
Indexing
Scopus