An Approach to Enhance Business Intelligence and Operations by Sentimental Analysis

Abstract

Sentimental analysis is rapidly getting inducted into businesses as a direct result of the technology growth in every sector owing to globalization and industry 4.0. Sentimental analysis which is also known as opinion mining is used in identifying and analyzing text based on the tone that was conveyed by the person which can be categorized broadly into positive, negative and neutral. Businesses can utilize sentimental analysis to tap insight important insights regarding companies, organizations, people, trends and services. With the vast amount of Big Data increasing every day, especially from social media such as Twitter, Facebook etc. businesses can utilize sentimental analysis. This paper thus focuses on implementing machine learning models in Python to perform sentimental analysis from twitter tweets as a viable approach to enhance business intelligence, improve decision marking and target effective operations. The data used in this analysis is obtained from Kaggle collections of COVID-19 twitter dataset. This paper also discusses the various types of applications for sentimental analysis in business and their benefits. The findings from this paper will help improve understanding sentimental analysis for businesses and their practicality in real world scenarios as Big Data advances whilst business intelligence of companies rigorously demands outshining competitive advantage. © 2021, Success Culture Press. All rights reserved.