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Topical analysis of migration coverage during lockdown in India by mainstream print media

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  • Swati Agarwal
  • Sayantani Sarkar

Abstract

Implementing countrywide lockdown measures in India, from March 2020 to May 2020 was a major step to deal with the COVID -19 pandemic crisis. The decision of country lockdown adversely affected the urban migrant population, and a large section of them was compelled to move out of the urban areas to their native places. The reverse migration garnered widespread media attention and coverage in electronic as well as print media. The present study focuses on the coverage of the issue by print media using descriptive natural language text mining. The study uses topic modelling, clustering, and sentiment analysis to examine the articles on migration issues during the lockdown period published in two leading English newspapers in India- The Times of India and The Hindu. The sentiment analysis results indicate that the majority of articles have neutral sentiment while very few articles show high negative or positive polarity. Descriptive topic modelling results show that transport, food security, special services, and employment with migration and migrants are the majorly covered topics after employing Bag of Words and TF-IDF models. Clustering is performed to group the article titles based on similar traits using agglomerative hierarchical clustering.

Suggested Citation

  • Swati Agarwal & Sayantani Sarkar, 2022. "Topical analysis of migration coverage during lockdown in India by mainstream print media," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-19, February.
    • Handle: RePEc:plo:pone00:0263787
    DOI: 10.1371/journal.pone.0263787
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    References listed on IDEAS

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    1. Allen J. Scott, 2009. "World Development Report 2009: reshaping economic geography," Journal of Economic Geography, Oxford University Press, vol. 9(4), pages 583-586, July.
    2. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    3. Ramit Debnath & Ronita Bardhan, 2020. "India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-25, September.
    4. Jan Breman, 2020. "The Pandemic in India and Its Impact on Footloose Labour," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 63(4), pages 901-919, December.
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    Cited by:

    1. Shehla Rashid Shora & Arshia Arya & Joyojeet Pal, 2023. "Institutional isomorphism in corporate Twitter discourse on citizenship and immigration in India and the United States," Global Policy, London School of Economics and Political Science, vol. 14(5), pages 938-948, November.

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