Text-Based Emotion Analysis Approach for Understanding Human Behavior

To identify that whether type of text is negative, positive or neutral, emotion analysis is performed. NLP-Natural language processing and various learning algorithms were used in a sentiment analysis methods for text analysis to provide weighted sentiment ratings to subjects, entities, concepts, and groups at the same time as a phrase or sentence to identify human behavior. To scale opinion, do intense studies, monitor the complete and review the current, and assess consumer experiences, data analysts in significant corporations employ sentiment analysis. Data analytics companies frequently provide third-party content analysis within their own customer experience, social media monitoring or various platforms in order to obtain appropriate insights to their customers. In this work text based emotion analysis approach is used to understand human behavior. For this used authorized dataset of twitter texts and apply various classifiers like Linear SVC, Random Forest (RF) and DL based RoBERTa method.