Analyzing the depression and suicidal tendencies of people affected by COVID-19's lockdown using sentiment analysis on social networking websites. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Sharma, Sparsh; Sharma, Surbhi
• Is Part Of: Journal of statistics & management systems. Volume 24:Issue 1(2021)
• Page Start: 115
• Page End: 133
• Publication Date: 2021-01-02
• Subjects: 68; Coronavirus -- COVID-19 -- Facebook -- Lockdown -- Sentiment analysis -- Suicidal tendencies -- Twitter; Statistics -- Periodicals; Mathematical models -- Periodicals; Mathematical models; Statistics; Periodicals; 519.5
• DOI: 10.1080/09720510.2020.1833453
• Languages: English
• ISSNs: 0972-0510

Abstract

Abstract: Coronavirus 2019, also known by name Corona Virus Disease (COVID-19), is the newer type of pandemic and communicable disease that has erupted and is spreading at alarming rates. This pandemic has shocked the whole world and has affected all the sectors ranging from healthcare, science, economy, government, trade. The rate and scale at which this virus is spreading are so rapid that it has become almost impossible to contain and scientists, and researchers across the world are working hard to stop and contain its spread. Till now, since there is no cure and vaccines for COVID-19, it is the need of the hour to find out ways and techniques to combat and contain its impact and spread. It has claimed the lives of around three lakh people, and this number is still growing. It has impacted not only the health of people but also it has shattered the economies of various countries leading to shutting down of various companies and making people jobless. Lockdown has been imposed by the government of various countries to contain the spread of this pandemic. This lockdown has forced the people to remain at their homes jobless, without money and food. The probability of developing depression and suicidal tendencies among people is growing. It is very important to identify such people and to provide the required assistance in this hour of emergency. In this article, a Sentiment Analysis Framework has been proposed which will extract the emotions and sentiments of people from the social networking website like twitter and report the location as well as the required available details to the authority to save the lives of people from this pandemic.