In this digital era, almost everyone can share their thoughts over the internet through texts in messages, posts or blogs, and people often convey emotions of different sorts as well. Sometimes it is about mental health, review about a bad product or simply opinions on different aspects of the modern world. Because of its massive popularity, emotion detection from text has become a burning topic for researchers. This review paper tries to provide understanding of different levels in various emotion models, different works that have been done in emotion identification from text and how it works along with introduction to various available datasets. Also how different models like LSTM, CNN, BERT and so on are utilized by researchers to provide better results in text-based emotion detection is also discussed with their advantages and disadvantages. Finally this paper also points out different obstacles and challenges that lie in the study of emotion extraction from text.