Sentiment Analysis using Naïve bayes Algorithm

Authors

  • Pramod M Mathapati Dept. of Computer Science, Gogte Institute of Technology, VTU, Belagavi, India
  • AS Shahapurkar Dept. of Computer Science, Gogte Institute of Technology, VTU, Belagavi, India
  • KD Hanabaratti Dept of Computer Science, Gogte Institute of Technology, VTU, Belagavi, India

DOI:

https://doi.org/10.26438/ijcse/v5i7.7577

Keywords:

Sentiment Analysis, Modified k means, NLP, Opinion Mining

Abstract

Sentiment analysis is trending topic of research which works on data which is got from review websites, social networks. Today users having common platforms like Blogs, micro blogs, review sites, twitter and other social networks through which they can post their feedbacks. Organizations use Sentiment Analysis to understand user’s reviews and feedbacks about the product which they have released. In this project development of a Sentiment analysis using a generic method which can be applied for sentiment analysis as well as Emotional Analysis, product reviews is done based on Naïve Bayes classifier method. Naive bayes Classifier is the better choice for Sentiment Analysis as it is more efficient and gives Quick results compared to other techniques such as Support Vector Machine and Maximum Entropy.

References

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Published

2025-11-11
CITATION
DOI: 10.26438/ijcse/v5i7.7577
Published: 2025-11-11

How to Cite

[1]
M. Pramod M, A. Shahapurkar, and K. Hanabaratti, “Sentiment Analysis using Naïve bayes Algorithm”, Int. J. Comp. Sci. Eng., vol. 5, no. 7, pp. 75–77, Nov. 2025.

Issue

Vol. 5 No. 7 (2017): IJCSE July Edition

Section

Review Article

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