Ensemble model for Twitter sentiment analysis
Chintan Jethalal Dedhia, Jyoti Ramteke · 2017 International Conference on Inventive Systems and Control (ICISC) · 2017
Sentiment mining from sources like Twitter which contain informal texts is needed as there is prominent information and vast amount of data to be analyzed, understood and experimented. There has been a lot of research in this area to get the semantic information from this domain and to create better prediction in terms of Sentiment classification. We present a novel approach which provides an ensemble model for Classification taking SVM as base learner and Adaboost as the Ensemble Boosting algorithm. We show the Precision, Recall and F1 score by comparing it with the baseline SVM algorithm.