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Sentiment analysis of social media data evolved from COVID-19 cases - Maharashtra
Advanced Data Mining Tools and Methods for Social Computing ; : 51-66, 2022.
Article in English | Scopus | ID: covidwho-1750922
ABSTRACT
One of the most significant threats to today's global society is COVID-19. Due to the fear of the nCoV-19 virus and increasing infection and death rates, complete lockdowns are enforced in the whole world. Due to this contagious disease, physical communication is very difficult and risky, so the best option for communication is connection via digital media. With the constantly growing number of media platforms, India has shrunk due to the increasing communication and exchange of information. These digital platforms turned out to be most effective as regards quicker communication during the pandemic. The present study on the usage of social media during a time of pandemic addresses effective ways of usage of social media for public communication with emergency organizations, such as police, during lockdown. This information will help to identify people who are careless, cautious, and neutral towards this situation. Moreover, we discuss how to identify various emotions of people before, during, and after this crisis situation using naive Bayes and K-means clustering for clustering of tweets or comments on Twitter and Facebook and find trends using social media analytics. © 2022 Elsevier Inc. All rights reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Advanced Data Mining Tools and Methods for Social Computing Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Advanced Data Mining Tools and Methods for Social Computing Year: 2022 Document Type: Article