Sentimental Data Analysis-To Predict the User Emotions

Abstract

Creating a survey website that automatically updates information by analyzing data from social media is an innovative approach to gathering user feedback. In this project, data is collected from users through an Application Programming Interface (API), and the sentiment of the data is predicted as either positive or negative emotions of text. Neutral emotions are determined through a polarity score, which indicates the percentage of text emotions in a collected set of data. This method of predicting user data helps improve user understanding and satisfaction by identifying their needs and preferences directly from a large set of users.