Bibliometric and Text Mining Analysis of SDGs Governance Research

نوع المستند : المقالة الأصلية

المؤلف

Associate Professor- Planning Techniques Center – Institute of National Planning.

المستخلص

This paper presents a comprehensive analysis of the research on governance for the Sustainable Development Goals (SDGs) using bibliometric and text mining techniques. The study collected 6,341 articles from the Web of Science Core Collection database from January 2016 to December 2022. Bibliometric analysis revealed an increasing trend in publications related to SDGs governance, with a peak of 1,410 articles in 2022. The analysis also identified the top contributing countries, institutions, subject categories, and sources in the field. Text mining analysis employed topic modeling, specifically latent Dirichlet allocation (LDA), to identify key themes and topics within the collected articles. The findings highlighted the importance of engaging diverse stakeholders, achieving the SDGs, addressing environmental challenges, identifying research gaps, utilizing qualitative analysis methods, and exploring the relationship between governance and sustainability. The analysis also emphasized the significance of gender equality, corporate social responsibility, decision support systems, education policies, water resource management, and green innovation for sustainable development. The results provide valuable insights into the research landscape and hotspots in SDGs governance, facilitating evidence-based decision-making and future research directions.
 

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المراجع

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