ANALYSIS OF TWITTER DATA USING MACHINE LEARNING ALGORITHMS

Sentiment analysis is one among the distinguished fields of knowledge and pattern mining that deals with identification sentiment within text. The main challenges in are word ambiguity multi polarity. problem to define polarity because for words context dependent. tweets initially preprocessed. preprocessing includes removal stop words, lower case conversion. then passed feature extraction techniques. Then data splitted as training testing data. trained different machine learning algorithm like Naive Bayes. Support Vector machine, Random forest, Decision Tree k-NN algorithm. accuracy obtained using random Tree, Logistic regression 80%, 77%, 72%, 61% ,56% 78%. naïve bayes has achieved a better when compared other KEYWORDS: SVM, bayes, tree, forest