Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach - Joshi, Ashwini M; Prabhune, Sameer (International Journal of Computer Sciences and Engineering, 2019)
World Wide Web is the largest source of information and huge information is available on the net. It is the growing tendency in users to express their opinions or thoughts using public opinion sites. Analysing all these opinions manually becomes challenging task so if we can develop the automated system to analyse what people want to say about any product, political party or any other thing it would be of great help. In this work we are trying to make readers life easier by providing the polarity of the reviews from user in automated way with better accuracy. The hybrid model is built using XGBoost and Logistic Regression classifiers and the performance of the hybrid model is compared to both the static models. As per expectation the hybrid model is performing better.