Abstract
One of the key territories of NLP is Sentiment Analysis, the capacity to comprehend emotional tones in speech and text.
This Systematic Literature Review has focused on papers between 2015 to 2020, taken from trusted and credible database such as IEEE Xplore, Science Direct and Springer. A total of 70 papers have been chosen for this review.
This SLR approach is followed to get an effective insight on various work being done in this research field using Machine learning techniques: supervised or unsupervised. Different research questions have been looked up and discussed.
The result shows that most of the work have used SVM for classification techniques and accuracy as the performance metrics.
Also most of the dataset are yielded from e-commerce sites for product reviews, reviews in form of tweets from twitter and in various other fields like hospitality reviews, movie reviews and other social networking sites opinions.
Key words: SVM, Machine Learning, SLR
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