India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling.

ABSTRACT: India locked down 1.3 billion people on March 25, 2020, in the wake of COVID-19 pandemic. The economic cost of it was estimated at USD 98 billion, while the social costs are still unknown. This study investigated how government formed reactive policies to fight coronavirus across its policy sectors. Primary data was collected from the Press Information Bureau (PIB) in the form press releases of government plans, policies, programme initiatives and achievements. A text corpus of 260,852 words was created from 396 documents from the PIB. An unsupervised machine-based topic modelling using Latent Dirichlet Allocation (LDA) algorithm was performed on the text corpus. It was done to extract high probability topics in the policy sectors. The interpretation of the extracted topics was made throug

SUBMITTER: Debnath R 

PROVIDER: S-EPMC7485898 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature