Files and links (1)
CC BY V4.0, Open Access
Journal article
Discovering topics and trends in biosecurity law research: A machine learning approach
One health, Vol.20, 100964
2025
Abstract
This study employed machine learning techniques, specifically Latent Dirichlet Allocation (LDA), to analyze 559 articles on biosecurity legislation from 1996 to 2023. The LDA model identified nine key research topics, including Agricultural Management and Production, Biosafety and Environmental Impact, Biological Invasion and Regulation, Biosecurity Legislation and Prevention, Agriculture and Environmental Relations, Virus Infection and Governance, Health Risk Assessment and Detection, Disease Prevention and Biotechnology, and Policy Control and Research. The findings reveal significant trends: an increasing focus on Biosecurity Legislation and Prevention and a declining interest in Agricultural Management and Production. Geographically, Australia, Canada, and the United States lead in biosecurity research, exhibiting diverse research topics. Journal-level analysis highlights central topics such as Agricultural Management and Production, Biosecurity Legislation and Prevention, and Health Risk Assessment and Detection. This study's use of LDA reduces subjective bias, providing a more objective analysis of global biosecurity legislation literature. The research underscores the importance of expanding geographical scope, integrating advanced machine learning models, adopting interdisciplinary approaches, and assessing policy impacts to enhance biosecurity strategies globally.
Details
- Title
- Discovering topics and trends in biosecurity law research: A machine learning approach
- Authors/Creators
- Yang Liu
- Publication Details
- One health, Vol.20, 100964
- Publisher
- Elsevier B.V.; AMSTERDAM
- Number of pages
- 14
- Identifiers
- 991005726577407891
- Copyright
- © 2025 The Author.
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
3 File views/ downloads
18 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Citation topics
- 1 Clinical & Life Sciences
- 1.104 Virology - General
- 1.104.1882 Livestock Viral Threats
- Web Of Science research areas
- Infectious Diseases
- Public, Environmental & Occupational Health
- ESI research areas
- Clinical Medicine