Sentiment analysis and opinion mining via microblogging in social media like: Twitter

This research is a study of microblogging on social websites such as Twitter and shows the techniques of emotion detection and sentiment analysis for the same. This research has three objectives. The first objective is a discussion about how to extract and classify emotions in tweets using the unigram feature extractor with word presence or word frequency as a factor of extraction. High accuracy of classification is obtained when considering the word presence as a factor of extraction. Moreover, one can obtain high accuracy also by using word frequency as a factor of extraction when supplying the test data on training corpora of tweets in the case of multi-domain tweets. The second objective is the extraction and classification of the emotions of tweets using n-gram (1