SENTIMENT ANALYSIS USING MACHINE LEARNING APPROACH NEIVE BAYES CLASSIFICATION WITH STANDARD OPENION KEYWORD DICTIONARY
| Author(s) | : | Nikita Kakdiya, Prof. Debalina Nandy |
| Institution | : | Nikita Kakdiya, Student, Department of Computer Engineering,R.K.University |
| Published In | : | Vol. 1, Issue 11 — November 2014 |
| Page No. | : | 220-223 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
This Sentiment Analysis is determining opinions, emotions and attitudes of a writer. Sentiment analysis taskclassifying the polarity of a given text at the document or sentence is positive, negative or neutral. In this paper define astandard opinion keyword dictionary.in there positive and negative word list. Each word to allocate hand ranked valuein between +5 to -5.we purpose an aspect of identification or classification task for machine learning approach forsentiment sentences in review, comments, or tweet. Supervised classification algorithms, Naïve Bayes classifier is use tofinding an opinion positive, negative or neutral polarity.
Nikita Kakdiya, Prof. Debalina Nandy, “SENTIMENT ANALYSIS USING MACHINE LEARNING APPROACH NEIVE BAYES CLASSIFICATION WITH STANDARD OPENION KEYWORD DICTIONARY”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 1, Issue 11, pp. 220-223, November 2014.
