Emotion Recognition in Text has received profound attention in recent years especially with the proliferation of the social media platforms and advancements in human-computer interaction. In the past decade, the research in this area has been propelled by the new developments in deep learning and multimodal integration. This article discusses affect detection in text and reviews recent work conducted in the field of automatic detection and classification of emotions in text. We also discuss how the opinion mining, sentiment analysis and emotion classification differ from each other. We delve into various theories and models of emotion recognition in text. Different approaches for recognizing emotions in text are discussed outlining their strengths and weaknesses. We discuss different contemporary approaches for emotion detection and outline the major challenges in the field.