Status updates Sorting and Analyzing Data using Machine Learning Models

Abstract

Every day, people utilize several social media sites to disseminate information about what's hot in the world.
Twitter, in particular, is used extensively by individuals all over the globe to voice and disseminate their
thoughts and ideas. This has a profound effect on many issues, and individuals do it to express their agreement
or disagreement. Logistic Regression, Decision Tree, and XGBOOST from Machine Learning, and TF-IDF and
Bag of Words from Natural Language Processing, are the five basic methodologies utilized when thinking about
Twitter sentiment analysis. First, raw data is prepared for analysis, then a word cloud is constructed, features are
extracted, and finally, a comparison of multiple Machine Learning models is generated. Preprocessing,
visualization, and feature extraction are some of the most important aspects of machine learning. Preprocessing,
visualization, and feature extraction are some of the most important aspects of machine learning.