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Analyzing Tweets for Better Decision-Making using Machine Learning


Hazzaa N. Alshareef and Imran Usman


Vol. 21  No. 10  pp. 119-124


The adaptive advancement in internet technology convince individual to exchange the information. One of the most influential platforms to share contents over the World Wide Web is the social media. Social media includes Blogs, content forums, social networking sites and virtual environments. These are quickly becoming one of the most persuasive sources of news, economies, businesses, thoughts, emotions, feedback and reviews. The ceaseless swift development of electronic Arabic contents in social media diverts and in Twitter especially represents a chance for opinion mining analysis. This work represents a novel Na?ve Bayes classification framework to classify and analyze positive, negative and neutral Arabic tweets regarding Saudi Electronic University.


Arabic Tweets, Na?ve Bayes Classifier. Sentiment Analysis