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Education hubs in Qatar and the United Arab Emirates: Analysis of discursive constructions using Latent Dirichlet Allocation

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  • Adam, Edmund
  • Adam, Neil

Abstract

Advanced techniques for linguistic analysis provide the opportunity to extract meanings from the available documents on education hubs. We use Latent Dirichlet Allocation (LDA), a topic modelling method for natural language processing and big data mining, to analyze the discourse of education hubs in Qatar and the United Arab Emirates (UAE). Our data derive from a corpus of academic literature, non-peer-reviewed articles, and policy documents. The analysis shows that education hubs have been at the core of efforts to transition from a hydrocarbon-based economy to a knowledge economy. The analysis also shows that education hubs have been increasingly associated with the two countries’ efforts to achieve regional leadership in overlapping geopolitical spheres of influence. Describing the situation as a ‘constructive rivalry’, we highlight its geopolitical implications and we call attention to Knight, (2022) knowledge diplomacy whereby the two countries can use education hubs as a mechanism for exercising leadership in promoting peace and development in the broader region of the Middle East.c.

Suggested Citation

  • Adam, Edmund & Adam, Neil, 2024. "Education hubs in Qatar and the United Arab Emirates: Analysis of discursive constructions using Latent Dirichlet Allocation," International Journal of Educational Development, Elsevier, vol. 107(C).
  • Handle: RePEc:eee:injoed:v:107:y:2024:i:c:s0738059324000567
    DOI: 10.1016/j.ijedudev.2024.103034
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    References listed on IDEAS

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    1. Cal Clark & Charles E. Menifield & LaShonda M. Stewart, 2018. "Policy Diffusion and Performance-based Budgeting," International Journal of Public Administration, Taylor & Francis Journals, vol. 41(7), pages 528-534, May.
    2. Knight, Jane, 2024. "The evolution of contemporary education hubs: Fad, brand or innovation?," International Journal of Educational Development, Elsevier, vol. 104(C).
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