A Survey of Textual Emotion Detection

Abstract

Emotion detection in text is a research field that gained an extensive interest recently. The advancement in communication networks and the spread usage of social web is the reason of massive amount of emotions that can be extracted frequently. The extraction and analysis of such emotions provides a powerful tool in detecting and recognizing the feelings, and this provides many advantages in diverse areas. In this survey, we focused on the textual emotion detection as a task of sentiment analysis. This survey explored the latest state of art approaches for emotion detection in text, and discussed their classification according to the used techniques, the used emotional model and the different used datasets. The outcome of this paper tends to highlight the limitation and gaps of these recent works and direct the possible future research to fulfill these gaps in this increasingly developed field.