Textual information analysis on user’s emotion in social media using machine learning technique / Ahmad Danial Musana

The world has been shocked by Covid-19 and it has caused various human emotions posted on social media due to many aspects such as vaccination, number of daily Covid-19 cases and many more. This project is about analysis on user’s emotion based on textual information in social media using machine learning techniques. The objectives of this project is to develop classification model of analyzing user’s emotion based on textual information, to compare the accuracy of each machine learning technique and to test the classification performance of developed model using evaluation metrics. This machine learning techniques applied includes Artificial Neural Network (ANN) and Naïve Bayes. The project also contains comparison of machine learning technique and three type of data split for testing and evaluation metrics is used to check the precision, recall and F1 – Score. Testing result shows that, the NB model outperform ANN with 59% accuracy.