Analyzing Unemployment in India during COVID-19 Pandemic

Ashika Deb

Miranda House, University of Delhi, India

Unemployment gives birth to several social and economic problems and the COVID-19 pandemic has exposed and exacerbated existing inequities in the labour market heightening this issue. The pandemic has changed the course of the world and due to drastic economic changes, the state of employment has inevitably changed globally, more so in developing countries. Power and privilege are major determinants of who is at risk for precarious work, with historically marginalized communities being disproportionately vulnerable to these job conditions. The pandemic worsened the situation for millions who were already dangling between the line of poverty and helplessness leading to massive job losses and a huge talent vacuum. The problem of millions of helpless migrant labourers losing their homes due to lockdown and loss of jobs has also plagued India.

This project will focus on studying unemployment data in India and try to examine relations between the various factors that may have affected the unemployment during the pandemic. Towards this end, we will examine available data from official sources and utilize Wolfram Language capabilities to perform an exploration analysis and draw out meaningful statistics from them. Furthermore, we would like to perform sentiment analysis on twitter data related to COVID-19 and unemployment tweets to see how the public opinion has fared with regard to these two topics in recent times.

Analyzing Unemployment in India during COVID-19 Pandemic

Understanding employment during the time of COVID-19 from survey data


Sentiment analysis of COVID -19 and unemployment tweets


Conclusion


Keywords


Acknowledgment


References


Analyzing Unemployment in India during COVID-19 Pandemic

Understanding employment during the time of COVID-19 from survey data

Sentiment analysis of COVID -19 and unemployment tweets

Conclusion

Keywords

Acknowledgment

References

Understanding employment during the time of COVID-19 from survey data


Sentiment analysis of COVID -19 and unemployment tweets


Conclusion


Keywords


Acknowledgment


References
