This paper is published in Volume-7, Issue-3, 2021
Area
Machine Learning
Author
Tushar Baratam
Org/Univ
GITAM Institute of Science, Visakhapatnam, Andhra Pradesh, India
Pub. Date
02 June, 2021
Paper ID
V7I3-1621
Publisher
Keywords
Sentiment Analysis, Opinion mining, Logistic Regression, Machine Learning, Natural Language Processing

Citationsacebook

IEEE
Tushar Baratam. Sentiment analysis using Supervised Learning Methods, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Tushar Baratam (2021). Sentiment analysis using Supervised Learning Methods. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.

MLA
Tushar Baratam. "Sentiment analysis using Supervised Learning Methods." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.

Abstract

As the organisations are getting bigger and bigger the need to make well informed decisions are ever more important. To do that however you need data. But is data enough. How is one to interpret the data to their advantage? How is one meant to sift through all of the data to find the specific ones that are meant to be relevant to the task at hand. For that you need a all-in-one solution. One that can handle all of that for us. This project targets the online product reviews. For an organisation that aims to sell products through online platforms like Amazon, Flipkart and other require a way to analyse all the product reviews to get information on what is performing well and what isn’t. For that it is important that the sentiments are analysed where it predicts where the review is positive or negative and what aspects of the review are negative or positive. It needs to give a numerical and visual representation which is helpful when it required to present the data to someone. All of these issues are addressed with the help of this application. It is built in python using pre-existing well-known libraries. Which also means that it is verified by many.