Exploration and Correlation of Machine Learning Models through Option Mining of Airline Tweets
Sandra Saji, P G Archana, L Nitha · 2023
Twitter is a well-known and widely used social media platform since it enables users to share their ideas and opinions on any topic and also submit messages or comments from anywhere in the world. These reviews and opinions are examined using Sentiment Analysis tools. An NLP approach called sentiment analysis is used to categorize positive, negative, and neutral. In this research, we used machine learning methods such as SVM, Logistic Regression, and Random Forest to perform sentiment analysis on the Twitter Airline Dataset. Positive, negative, and neutral emotions are the three ways that emotions are conveyed. The primary objective of this paper is to check which Machine learning model gives the best accuracy. The experimental results show that Random Forest models provide the best accuracy that is 99.26%