Supervised Sentiment Analysis Algorithms (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Sentiment analysis is used to analyse customer sentiment by the process of using naturallanguage processing, text analysis, and statistics. A good customer survey understands thesentiment of their customers—what, how and why they’re saying it. Sentiment dataset can befound mainly in tweets, comments and reviews. Sentiment Analysis understands emotionswith the help of software, and it is playing an inevitable role in today’s workplaces.Sentiment analysis for opinion mining has become an emerging area where more researchand innovations are done. Sentiment or opinion analysis based on a domain is done usingseveral algorithms. Machine learning is a concept among this area. In this, the main focus ison the supervised sentiment analysis or opinion mining algorithms. Supervised learning is adivision coming under machine learning. Different methods of supervised learning andsentiment analysis algorithms are considered and their mode of functioning is studied. Mainfocus of this paper is on the recent trends of research and studies for sentiment classification,taking into consideration the accuracy of different algorithmic techniques that can beimplemented for accurate prediction in sentiment Analysis.