Sentiment Analysis of Lockdown in India During COVID-19: A Case Study on Twitter | Java IEEE Final Year Project 2021 - 2022.
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Project Title:
Sentiment Analysis of Lockdown in India During COVID-19: A Case Study on Twitter.
Project Base paper:
With the rapid increase in the use of the Internet, sentiment analysis has become one of the most popular fields of natural language processing (NLP). Using sentiment analysis, the implied emotion in the text can be mined effectively for different occasions. People are using social media to receive and communicate different types of information on a massive scale during COVID-19 outburst. Mining such content to evaluate people’s sentiments can play a critical role in making decisions to keep the situation under control. The objective of this study is to mine the sentiments of Indian citizens regarding the nationwide lockdown enforced by the Indian government to reduce the rate of spreading of Coronavirus. In this work, the sentiment analysis of tweets posted by Indian citizens has been performed using NLP and machine learning classifiers.
REFERENCE:
Prasoon Gupta , Sanjay Kumar, R. R. Suman, and Vinay Kumar, “Sentiment Analysis of Lockdown in India During COVID-19: A Case Study on Twitter”, IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, VOL. 8, NO. 4, AUGUST 2021.
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