Impact of COVID 19 on Indian Migrant Workers: Decoding Twitter Data by Text Mining
Pooja Misra () and
Jaya Gupta ()
Additional contact information
Pooja Misra: Birla Institute of Management Technology
Jaya Gupta: Birla Institute of Management Technology
The Indian Journal of Labour Economics, 2021, vol. 64, issue 3, No 10, 747 pages
Abstract:
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.
Keywords: Covid19; Migrant workers; Indian economy; Lockdown; Plight; Policy measures (search for similar items in EconPapers)
JEL-codes: E0 E61 E66 J21 J61 J68 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s41027-021-00324-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:ijlaec:v:64:y:2021:i:3:d:10.1007_s41027-021-00324-y
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/41027
DOI: 10.1007/s41027-021-00324-y
Access Statistics for this article
The Indian Journal of Labour Economics is currently edited by Alakh Sharma
More articles in The Indian Journal of Labour Economics from Springer, The Indian Society of Labour Economics (ISLE) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().