At the present time, social media has become an important popular communication medium among all online suffers. Twitter is one of the most popular social networking services where thoughts and opinions about various aspects and activities can be shared by the millions of users. Social media websites are rich sources of data for opinion mining. Such data can be applied for sentiment analysis. Sentiment analysis is the study of human behavior by extracting user opinion and emotion form plain text. Among machine learning techniques, Support Vector Machine (S.V.M) classifier and K-Nearest Neighbour (K-N.N) classifier is used in this system. The system provides the analytical results of education, business, crime and health for Educational Authorities, Economists, Government Organizations needs and Health. And then, the system predicts the conditions of selected ASEAN countries (Malaysia, Singapore, Vietnam and Myanmar) according to the tweets. In this system, accuracy, precision, recall and f1-score is also compared by using these two classifiers.
Naw Naw (2018); Twitter Sentiment Analysis Using Support Vector Machine and K-NN Classifiers; International Journal of Scientific and Research Publications (IJSRP)
8(9) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.8.10.2018.p8252