An effective architecture for prediction of severity levels of anxiety,depression,stress during the dissemenation of Social media Infodemic at the times of COVID-19 using multiclass classifier
Garima Joshi, Dr.Prashant Panse
During the COVID-19, an infectious disease caused by the SARS-CoV-2 virus that spread across the world ,a huge amount of population got affected. It is directly affected to the mental and physical health of every stage of age and hence thereby immensely affects the work –life balance either directly or indirectly. Almost one year was the life changer phase of everyone’s life. The mental state was affected due to financial issues, relational issues, environmental issues and some constrainable issues related to prevention from COVID-19.Some sort of pressure of survival in the profession and personal life is the big challenge for everyone ,nowadays. During the lockdown period, frequent access of news channels, online and social media give birth to anxiety and stress .Increase in the media sources and variety of information presented on the single topic leads to develop multiple questions in our minds .Infodemic plays the vital role as the various information sources like news channels, social media, E- newspapers provides excessive information out of which some are essential for us but some information are un-essential and such un-important information has become the high risk for the mental health of individuals. In this research, we will attempt to analyze the various types of media content impacting mental health of the individual during COVID-19 therefore affecting the work life balance. As a part of this, we analyze different social media contents which are the part of infodemic and will apply data science techniques to analyze that the which part of information is misinformation in the terms of affecting mental state of anyone .
Article Details
Unique Paper ID: 157186

Publication Volume & Issue: Volume 9, Issue 6

Page(s): 106 - 113
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