000			01451nam a22001937a 4500
003			OSt
005			20220107122853.0
008			190705b xxu||||| |||| 00| 0 eng d
040			_cIIITMK
100			_aAthira B U (92217007) _916125
245			_aSocial media analytics: _bBlog analytics for finding vulnerability
300			_aMSC DA 2017-2019
500			_aSentiment analysis in natural language processing (NLP) is an important task where the text content have several opinions about events, product and movie reviews, trading, marketing, etc. It is an automated process of understanding an opinion about a given subject from written or spoken language. In recent studies, researchers have performed the hand-crafted features in sentiment analysis and machine learning methods such as support vector machines, naive Bayes, conditional random field, maximum entropy method, etc. but sentiment analysis will be very difficult for agglutinative language like Malayalam. The proposed work deals with the categorization of blogs according to its vulnerability, and specify them as Very Good, Good, Less Vulnerable, Vulnerable, Highly vulnerable. Keywords : Support Vector Machine, Malayalam, Sentiment Analysis, Natural Language Processing
502			_bMSC DA _c2017-2019 _dINT _eDr Manoj Kumar T K
650			_aSUPPORT VECTOR MACHINE _916126
650			_aSENTIMENT ANALYSIS _916127
650			_aNATURAL LANGUAGE PROCESSING _916128
942			_2ddc _cPR
999			_c6558 _d6558