ArticlePloS one2020
India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Trial
- Research on New Methods of Topic Mining and Topic Prediction for Medical Preprints on Emerging Infectious Diseases.Cureus · 2025Article
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- Topic modeling and evolutionary trends of China's language policy: A LDA-ARIMA approach.PloS one · 2025Article
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- A 30-Year Review on Nanocomposites: Comprehensive Bibliometric Insights into Microstructural, Electrical, and Mechanical Properties Assisted by Artificial Intelligence.Materials (Basel, Switzerland) · 2024Review
- Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach.JMIR medical informatics · 2023Article
- Evaluating health policies with subnational disparities: a text-mining analysis of the Urban Employee Basic Medical Insurance Scheme in China.Health policy and planning · 2023Article
- Contrasting semantic and sentimental features between Chinese and American economic news discourse in the epidemic era: A corpus-based critical discourse analysis.Social sciences & humanities open · 2023Article
- Quantitative Evaluation of China's Ecological Protection Compensation Policy Based on PMC Index Model.International journal of environmental research and public health · 2022Article
- Exploring Sentiment and Care Management of Hospitalized Patients During the First Wave of the COVID-19 Pandemic Using Electronic Nursing Health Records: Descriptive Study.JMIR medical informatics · 2022Article
- The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19.Social science & medicine (1982) · 2022Review
- Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models.Energy policy · 2022Article
- Topical analysis of migration coverage during lockdown in India by mainstream print media.PloS one · 2022Article
- Responses to COVID-19 with probabilistic programming.Frontiers in public health · 2022Article
- Article
- LDA-based topic modeling for COVID-19-related sports research trends.Frontiers in psychology · 2022Article
- Tools for public health policy: nudges and boosts as active support of the law in special situations such as the COVID-19 pandemic.Globalization and health · 2021Article
- COVID-19 related interdisciplinary methods: Preventing errors and detecting research opportunities.Methods (San Diego, Calif.) · 2021Review
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2 authors.
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No grant is acknowledged in the PubMed record.
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 through a nudge theoretic lens to derive the critical policy heuristics of the government. Results showed that most interventions were targeted to generate endogenous nudge by using external triggers. Notably, the nudges from the Prime Minister of India was critical in creating herd effect on lockdown and social distancing norms across the nation. A similar effect was also observed around the public health (e.g., masks in public spaces; Yoga and Ayurveda for immunity), transport (e.g., old trains converted to isolation wards), micro, small and medium enterprises (e.g., rapid production of PPE and masks), science and technology sector (e.g., diagnostic kits, robots and nano-technology), home affairs (e.g., surveillance and lockdown), urban (e.g. drones, GIS-tools) and education (e.g., online learning). A conclusion was drawn on leveraging these heuristics are crucial for lockdown easement planning.
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