The Internet and communication technologies of today are extremely fast and dynamic. In the age of mobile phones and computers, the use of different communication channels, such as cell phones and computers, is very common. This project develops an Emotion Detection Model that takes sentence-level emotion into account. In natural language processing, content-based classification problems include concepts from both machine learning and natural language processing. Our technique employs direct emotional keywords in text as a means of identifying emotions. In order to increase the accuracy of the detection, words and phrases containing emotion-affect were also considered. We have thought about emotions like happiness, sadness, anger, and so on to help us recognise emotion in text. Human beings actually use these expressions. They are important investigations, as their findings have the potential to better express human emotions and help facilitate interpersonal communication.

Keywords : SVM, Python, Emotion Detection, Testing.