Analyzing research trends of sentiment analysis and its applications for Coronavirus disease (COVID-19): A systematic review

Author:

Jain Vipin1,Kashyap Kanchan Lata1

Affiliation:

1. VIT Bhopal University, Madhya Pradesh, India

Abstract

COVID-19 epidemic is one of the worst disaster which affected people worldwide. It has impacted whole civilization physically, monetarily, and also emotionally. Sentiment analysis is an important step to handle pandemic effectively. In this work, systematic literature review of sentiment analysis of Indian population towards COVID-19 and its vaccination is presented. Recent exiting works are considered from four primary databases including ACM, Web of Science, IEEE Explore, and Scopus. Total 40 publications from January 2020 to August 2022 are selected for systematic review after applying inclusion and exclusion algorithm. Existing works are analyzed in terms of various challenges encountered by the existing authors with collected datasets. It is analyzed that mainly three techniques namely lexical, machine and deep learning are used by various authors for sentiment analysis. Performance of various applied techniques are comparative analyzed. Direction of future research works with recommendations are highlighted.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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