Emotion Classification of Social Media Posts using Artificial Intelligence and Machine Learning

Machines can nowadays understand almost any type of data and they can identify most of the patterns, but identification of emotions or emotion mining has always been a challenging task. Emotion analysis is one of the major research points which aims to classify the text according to the emotions detected. In this paper, we will be analyzing the categories of the emotions in the written text, audio, and videos/images, and the intensity of the emotions. By analyzing the emotions, we can understand the author's perspective on the text. Emotion mining has become a very important part of the online industry because it is one of the major points of customer satisfaction, helps in selecting online material to teach, recommends products based on user emotions, or can be used to detect if the user is undergoing through any mental stress or disorder. During this project, we will be studying and analyzing different approaches which were previously and currently being utilized for the detection of human emotions through data which is in text format. Also, different approaches along with different applications of emotion analysis are vast, we can use it in online shopping apps, to check for customer satisfaction, and it can be used in the field of medicine by doctors to understand the mental status and stress levels of the patient. Emotion analysis can also be used on social media platforms and marriage portals to check for genuineness and the intentions of a person.