Hybrid Data Mining Approach For Emotion Analysis

Social media plays a significant role in exploring opinions and emotions of the users based on day to day activities. Mining social network data regarding user's opinions and emotions is necessary to understand the user's behaviour and mentality. This research work proposes a hybrid data mining approach using K-Means clustering and Naive Bayes classification techniques to analyse the emotions in the tweets. Emotion type based classification and Cluster based classification process performed on the tweet emotion data set using Naïve Bayes classifier analyses the performance of the hybrid data mining approach using performance measures.