Sentiment analysis is a process of obtaining information by understanding, extracting, and processing textual data automatically. Naïve Bayes Classifier is a classification method using a simple probability model based on the use of the Bayes theorem with strong independent assumptions. Text association is obtained by approaching the calculation of the correlation value. In general, correlation values are used to express the relationship between two or more quantitative variables.
This repository contains scripts or source code about analyzing sentiment on mobile application reviews using the Naive Bayes Classifier algorithm. In this project, text association was also carried out to obtain important information from mobile application reviews. In addition, by using the oversampling technique, I was able to increase the accuracy of sentiment classification by up to 90%.