A Review on Subjectivity Analysis through Text Classification Using Mining Techniques
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 3
Abstract
The increased use of web for expressing ones opinion has resulted in to an enhanced amount of subjective content available in the Web. These contents can often be categorized as social content like movie or product reviews, Customer Feedbacks, Blogs, Communication exchange in discussion forums etc. Accurate recognition of the subjective or sentimental web content has a number of benefits. Understanding of the sentiments of human masses towards different entities and products enables better services for contextual advertisements, recommendation systems and analysis of market trends. The objective behind framing this paper to analyze various sentiment based classification techniques which can be utilized for quick estimation of subjective contents of Political reviews based on politicians speech. The paper elaborately discusses supervised machine learning algorithm: Naïve Bayes classification and compares its overall accuracy, precisions as well as recall values.
Authors and Affiliations
Ashwin Shinde, Mayuri Marawar, Minal Domke, Bhushan Manjre
Keywords
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- EP ID EP390288
- DOI 10.9790/9622- 0703013840.
- Views 147
- Downloads 0
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