An Emotion based Sentiment Analysis on Twitter Dataset

Sentiment Analysis (SA), which employs data mining techniques to extract information from text and locate knowledge that can be used to track public opinion on certain commodities and social or political events, is one of the newest and most intriguing topics of research. One of the hottest topics in human-machine interaction right now is emotion recognition. In addition to recognizing Twitter gestures, a current research field uses textual data to determine a person's emotional condition. The primary goal of research is to identify emotions in Twitter tweets. The suggested emotion identification system outputs one of the six emotion classes when tweets are submitted (happy, sad, angry, fear, surprise, disgust). The goal is to assemble a predictive analysis of user behavior as well as the attitudes and opinions of the general public on a range of world events. The suggested hybrid emotion identification system also does well with a fresh set of features.