Athira B U (92217007) <br/><br/>
Social media analytics:  Blog analytics for finding vulnerability 

 - MSC DA 2017-2019 
<br/><br/> Sentiment analysis in natural language processing (NLP) is an important task<br/>where the text content have several opinions about events, product and movie<br/>reviews, trading, marketing, etc. It is an automated process of understanding an<br/>opinion about a given subject from written or spoken language. In recent studies,<br/>researchers have performed the hand-crafted features in sentiment analysis and<br/>machine learning methods such as support vector machines, naive Bayes, conditional<br/>random field, maximum entropy method, etc. but sentiment analysis will<br/>be very difficult for agglutinative language like Malayalam. The proposed work<br/>deals with the categorization of blogs according to its vulnerability, and specify<br/>them as Very Good, Good, Less Vulnerable, Vulnerable, Highly vulnerable.<br/>Keywords : Support Vector Machine, Malayalam, Sentiment Analysis, Natural<br/>Language Processing 
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<br/><br/><label>Subjects--Topical Terms: </label><br/>SUPPORT VECTOR MACHINE<br/>SENTIMENT ANALYSIS<br/>NATURAL LANGUAGE PROCESSING