Emotion analysis of Twitter using opinion mining

With the rise in use of micro-blogging sites like Twitter, people are able to express and share their opinions with each other on a common platform. Currently all work in opinion mining research has quantified & assessed the expression of opinion as positive, negative or neutral values, we intend to categorize the opinion on the basis of five emotions, namely Happiness, Anger, Fear, Sadness & Disgust, which have been globally accepted & defined in human psychology. This paper presents a method to assess these identified types of emotions in a tweet using opinion mining. A two-step approach is proposed, where firstly, to identify the sentiment; we extract the opinion words (a combination of the adjectives along with the verbs and adverbs) in the tweets and subsequently use a novel algorithm to find the emotion values of opinion words. The initial results show that it is a motivating technique, which may find potential applications in business intelligence, government policy making, amongst others.