Sentiment Analysis of Tweeter Extracted Data Using Supervised Machine Learning
Keywords:
Microblogging, Twitter ,Sentiment Analysis ,Machine Learning AlgorithmsAbstract
Most of the social networks use the concept of opinion mining which indicate about the reviews of a particular thing. Here particular thing may be any movie review or any kind of show or writing. In this paper we have applied machine leaning algorithm to predict the sentiments about the tweets extracted. Supervised machine learning are best learning algorithms to use. Tweeter is the most popular Microblogging which attains maximum amount of attention in some interesting areas like stock exchange, movie reviews etc. In this paper we applied support vector machine, Naïve Bayes classifier and maximum entropy as supervised machine algorithm. The classification of data extracted from tweeter is essential and for this, qualities of unigram, bigram and hybrid is used. The results of the experiment shows some good results in terms of accuracy than other classifiers for movie reviews
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