Automatic Generation of Emotions for Social Networking Websites using Text Mining

The rapid growth of the World Wide Web has increased the online communication. The use of social networking sites is one of the important approaches for communication. In order to improve the textual methods of communication such as tweets, blogs and chat; it is needed to analyze the emotion of user by studying the input text. Much of the current work in this area of emotion recognition from text has typically focused on recognizing the polarity of sentiment (positive/negative). This paper presents a novel approach for emotion estimation from the text entered by user on social networking sites. The work proposed in this paper uses affective words and sentence context analysis methods for emotion recognition. Also for helping the users to effectively express their emotion, we have developed visual image generation approach that generates images according to emotion in text. The results of evaluations show that the proposed system obtains better results for emotion prediction than the existing methods.