通过文献计量分析揭示硕士学位的研究版图
Revealing the research landscape of Master's degrees via bibliometric analyses
AI总结：
本文将硕士项目演进视为自组织系统，提出一种基于学位论文的文献计量工作流，通过分析产出动态及概念、社会和智力结构，指导决策者评估项目优势与战略目标，并辅以案例验证。
摘要：
与其他人类机构一样，硕士项目的演进可被视为一个自组织系统，其底层结构与动态主要源于教职员工与学生的互动。由于这种演进中隐含的复杂行为，识别这些隐藏属性并非易事。尽管如此，我们认为该项目的研究产出（主要以学位论文为代表）可以服务于这一目的。对此类数据的文献计量分析能够揭示关于产出增长、合作网络，以及已确立的、小众的和新兴研究主题的可视化图谱等方面的洞察。因此，我们提出了一种文献计量工作流，旨在发现产出动态以及由硕士学位发展出的概念、社会和智力结构，以指导决策者更好地评估项目的优势并优先考虑战略目标。此外，我们报告了两个案例研究以说明所提出工作流的实现。最后，我们探讨了该方法应用于其他学术研究单位的可能性。
英文摘要：
The evolution of a Master's programme, like many other human institutions, can be viewed as a self-organising system whose underlying structures and dynamics arise primarily from the interaction of its faculty and students. Identifying these hidden properties may not be a trivial task, due to the complex behaviour implicit in such evolution. Nonetheless, we argue that the programme's body of research production (represented mainly by dissertations) can serve this purpose. Bibliometric analyses of such data can reveal insights about production growth, collaborative networks, and visual mapping of established, niche, and emerging research topics, among other facets. Thus, we propose a bibliometric workflow aimed at discovering the production dynamics, as well as the conceptual, social and intellectual structures developed by the Master's degree, in the interest of guiding decision-makers to better assess the strengths of the programme and to prioritise strategic goals. In addition, we report two case studies to illustrate the realisation of the proposed workflow. We conclude with considerations on the possible application of the approach to other academic research units.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
