Sentiment Analysis of News Headlines using Naïve Bayes Classifier
نویسنده
چکیده
The amount of user generated content is increasing day by day and it involves detection of opinions about particular topic or an object. Sentiment analysis is used to extract sentiments of people about products, moviews, political events etc. It identifies the viewpoint of opinion holder and polarity of the content i.e. positive negative or neutral. Given the large amount of news being generated these days through various websites, it is possible to mine the general sentiment of particular news. Nowadays many people read news online. People's perspective tends to undergo a change as per the news content they read. The majority of the content that we read today is on the negative aspects of various things e.g. rapes, thefts, corruption etc. Reading such negative news is spreading negativity amongst the people. The positivity surrounding the good news has been drastically reduced by the number of bad news. The objective of this work is to provide a platform for serving good news and create a positive environment. Keywords—Sentiment analysis,text mining,machine learning, naïve bayes.
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