Survey on Sentimental Analysis and Visualization of Reviews

Authors

  • Bhanu Chugh Dept. Of Information Technology, Bharati Vidyapeeth(Deemed to be University) College of Engineering, Pune, Maharashtra, India
  • Sejal Arya Dept. Of Information Technology, Bharati Vidyapeeth(Deemed to be University) College of Engineering, Pune, Maharashtra, India
  • Mayank Pandita Dept. Of Information Technology, Bharati Vidyapeeth(Deemed to be University) College of Engineering, Pune, Maharashtra, India
  • Tanmay Jain Dept. Of Information Technology, Bharati Vidyapeeth(Deemed to be University) College of Engineering, Pune, Maharashtra, India
  • GV Bhole Dept. Of Information Technology, Bharati Vidyapeeth(Deemed to be University) College of Engineering, Pune, Maharashtra, India

DOI:

https://doi.org/10.26438/ijcse/v8i8.3033

Keywords:

Opinion Mining, Sentimental Analysis, SVM, Tableau

Abstract

The time when the food ordering websites are filled with tons of review data regarding the quality and quantity of food. One can extract tons of conclusions while analyzing it. In this survey paper, we will study various techniques to analyze the data including algorithms like Naive Baye’s, SVM, etc. and their outcomes in the field of data mining and sentimental analysis. Sentimental analysis is a boon for the restaurant owners as they can restructure their unique selling points and services. Customers can indeed use the data to filter the restaurants according to the area, cuisines, dining time, etc. to make an opinion. Also, in the end, polarising the high-quality dataset into positive and negative vows to visualize it for the customers. Tableau the most majestic tool can help us to do the same. Working on emoticons as well as text will take us to a hard way to complete the study.

References

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Published

2020-08-31
CITATION
DOI: 10.26438/ijcse/v8i8.3033
Published: 2020-08-31

How to Cite

[1]
B. Chugh, S. Arya, M. Pandita, T. Jain, and G. Bhole, “Survey on Sentimental Analysis and Visualization of Reviews”, Int. J. Comp. Sci. Eng., vol. 8, no. 8, pp. 30–33, Aug. 2020.

Issue

Vol. 8 No. 8 (2020): IJCSE August Edition

Section

Survey Article

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