Changing Banking Business Model Using Sentiment Analysis

Authors

  • Shilpa BL Department of Computer Science, VVIET, Mysuru, India
  • Shambhavi BR Department of information Science, BMSCE, Bengaluru, India

DOI:

https://doi.org/10.26438/ijcse/v7i1.291295

Keywords:

Sentiment Analysis, Natural Language Processing, Unstructured data, Opinion Mining

Abstract

Social media accounts like blogs, Facebook, Twitter and online discussion sites provide an option for an individual to express his or her opinion. These opinions are usually unstructured data and these are huge in amount. These days a massive number of users collect these recommendations or reviews for products and services, based on which they make their choices. The process of extraction of this insight from unstructured web data can be handled by Natural Language Processing and Big Data Analytics techniques. In this paper, we propose a model to extract this unstructured data from various domains, and then convert it into structured format by using various supervised algorithms. Finally the opinions or sentiments of the users will be presented for further understanding. Based on which the organization can take the necessary step to improve the customer retention.

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Published

2019-01-31
CITATION
DOI: 10.26438/ijcse/v7i1.291295
Published: 2019-01-31

How to Cite

[1]
B. Shilpa and B. Shambhavi, “Changing Banking Business Model Using Sentiment Analysis”, Int. J. Comp. Sci. Eng., vol. 7, no. 1, pp. 291–295, Jan. 2019.

Issue

Vol. 7 No. 1 (2019): IJCSE January Edition

Section

Research Article

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