• shivani mangla
• Anamika Singh
• Ashlesha Gupta

With the recent developments in social media and e-commerce, sharing of reviews on any topic or product has also increased. It has provided a common room to the people for expressing their opinions on any product or topic. So it is important to analyze the sentiment of these reviews. The reviews corresponding to the product are beneficial for both businesspersons and customers. Business persons can use positive reviews for the upliftment of their product and also negative reviews on any product can help them to understand their products’ drawbacks which in turn will help them in improving its quality. To get the best results, the most accurate classification technique must be used. So far various sentiment classification techniques have been proposed. This paper focuses on comparing some of these techniques like Naïve Bayes, SVM and K-means on the basis of precision, recall, F-measure and accuracy.

Sentiment Analysis, Naïve Bayes, SVM, K-means

"A comparison between various sentiment classification techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.58-63, December-2018, Available :http://www.jetir.org/papers/JETIR1812809.pdf

"A comparison between various sentiment classification techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp58-63, December-2018, Available at : http://www.jetir.org/papers/JETIR1812809.pdf