Computational Approaches for Emotion Detection in Text

Abstract

Emotions are part and parcel of human life and among other things, highly influence decision making. Computers have been used for decision making for quite some time now but have traditionally relied on factual information. Recently, interest has been growing among researchers to find ways of detecting subjective information used in blogs and other online social media. This paper looks at emotion theories that provide a basis for emotion models. It shows how these models have been used by discussing computational approaches to emotion detection. The emotion detection architecture that we propose consists of two components, knowledge based approach and learning systems approach. We present a prototype based on an architecture that we have proposed and demonstrate some of the challenges involved in detecting emotions from text.