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Research Network Analysis, Agenda Mapping and Research Productivity Monitoring: Insights from a Higher Education in the Philippines

机译:研究网络分析、议程映射和研究生产力监控:来自菲律宾高等教育的启示

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Research is the fundamental role of a higher education institution or HEI in the Philippines to spur knowledge generation and transfer in the community. The collection of research and its activities can foster collaboration between academe and industry to contribute to economic development. As the institution’s collects its unstructured research data the challenge to determine its growing research areas, alignment to the research agenda suggested by the funding agency, authors topic of interest and the authors collaboration is challenging. This study aims to determine the growing research areas and its alignment to the harmonized research agenda suggested by the Department of Science and Technology (DOST) for 2017 and 2022, researchers’ topics or interest and authors collaboration from the collection of research outputs. Through the categorization of topic per paper the study finds out the growing areas of Technological Institute of the Philippines (TIP) and plot its research areas alignment to the DOST research agenda and visualize using the Tableau tools. Meanwhile, through social network analysis (SNA) with Gephi the study is able to show the authors collaboration networks and using the Latent Dirichlet Allocation (LDA) topic modeling technique can provide clusters of topics representing researchers’ topics of interest. Moreover, the visualization results can be a helpful tool for the research management and research decision and policy makers to recommend research area to focus and direction to increase research productivity.
机译:研究是菲律宾高等教育机构或HEI在促进社区知识生成和转移方面的基本作用。收集研究及其活动可以促进学术界和工业界的合作,为经济发展做出贡献。随着该机构收集其非结构化研究数据,确定其不断增长的研究领域、与资助机构建议的研究议程保持一致、作者感兴趣的主题和作者协作的挑战也越来越大。本研究旨在确定不断增长的研究领域及其与科技部(DOST)建议的2017年和2022年协调研究议程的一致性,研究人员的主题或兴趣,以及研究成果集合中的作者协作。通过对每篇论文的主题进行分类,本研究发现了菲律宾技术研究所(TIP)的增长领域,并根据DOST研究议程绘制了其研究领域,并使用Tableau工具进行可视化。同时,通过Gephi的社会网络分析(SNA),该研究能够显示作者的协作网络,并且使用潜在Dirichlet分配(LDA)主题建模技术可以提供代表研究人员感兴趣主题的主题集群。此外,可视化结果可以为研究管理和研究决策者提供有用的工具,以推荐研究重点和方向,提高研究效率。

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