Sentiment Classifier on E-Commerce Product Reviews Using Logistic Regression

Authors

  • Prof. Pradeep N. Fale  Assistant Professor, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India
  • Nikita Swain  UG Scholar, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India
  • Pranay Rahangdale  UG Scholar, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India
  • Nikhil Dhakate  UG Scholar, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India
  • Harshwardhan Bagde  UG Scholar, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India
  • Pranay Waghmare  UG Scholar, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India

Keywords:

Sentiment Analysis, python, IOT, positive, negative, neutral

Abstract

All the e-commerce sectors are dependent on product selling and engendering revenue via advertisements, promotions, and offers. The companies and brands fixate on analyzing reviews on the product by different buyers of different ages and countries. Through the machine learning techniques, it is now possible to analyze product review data of users of Amazon, Flipkart, Myntra. This paper is presented to show the conceptions and implementation to find sundry sentiments of customers buying products online. And with the avail of datasets, we will define the precision of the analysis.

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International Journal of Scientific Research in Science and Technology

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Published

2022-06-30

Issue

Volume 9, Issue 3, May-June-2022

Section

Research Articles

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How to Cite

[1]
Prof. Pradeep N. Fale, Nikita Swain, Pranay Rahangdale, Nikhil Dhakate, Harshwardhan Bagde, Pranay Waghmare, " Sentiment Classifier on E-Commerce Product Reviews Using Logistic Regression , International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 9, Issue 3, pp.40-51, May-June-2022.