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Impact of COVID 19 on Indian Migrant Workers: Decoding Twitter Data by Text Mining

Author

Listed:
  • Pooja Misra

    (Birla Institute of Management Technology)

  • Jaya Gupta

    (Birla Institute of Management Technology)

Abstract

The Coronavirus pandemic has induced a huge economic crisis. The norms of social distancing and consequent lockdown to flatten the curve of this infection has brought economic activity across the globe to a standstill. A mass exodus of workers from major urban centres of India to their native villages started. Mental, financial and emotional agony inflicted due to job-loss, lack of job and livelihood opportunities led to this. A massive macroeconomic crisis for the country with serious ramifications has consequently exploded. The present study explores and captures the diffusion and discovery of information about the various facets of reverse migration in India using Twitter mining. Tweets provide extensive opportunities to extract social perceptions and insights relevant to migration of workers. The massive Twitter data were analysed by applying text mining technique and sentiment analysis. The results of the analysis highlight five major themes. The sentiment analysis confirms the confidence and trust in the minds of masses about tiding through this crisis with government support. The study brings out the major macroeconomic ramifications of this reverse migration. The study’s findings indicate that a concentrated joint intervention by the State and Central Governments is critical for successfully tiding through this crisis and restoring normalcy. The subsequent policy measures announced by the government are being critically gauged. In addition, the authors have proposed measures to ameliorate this damage on the formal and informal sectors.

Suggested Citation

  • Pooja Misra & Jaya Gupta, 2021. "Impact of COVID 19 on Indian Migrant Workers: Decoding Twitter Data by Text Mining," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 64(3), pages 731-747, September.
  • Handle: RePEc:spr:ijlaec:v:64:y:2021:i:3:d:10.1007_s41027-021-00324-y
    DOI: 10.1007/s41027-021-00324-y
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    Citations

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    Cited by:

    1. Niladri Sekhar Dhar & Shreya Nupur & Meghna Dutta, 2022. "COVID‐19 Induced Income Loss among Migrant Workers: Evidence from Eight Villages of Bihar," Economic Papers, The Economic Society of Australia, vol. 41(4), pages 325-346, December.

    More about this item

    Keywords

    Covid19; Migrant workers; Indian economy; Lockdown; Plight; Policy measures;
    All these keywords.

    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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