Research frontier detection and analysis based on research grants information: A case study on health informatics in the US

Ye, Guanghui; Wang, Cancan; Wu, Chuan; Ze, Peng; Wei, Jinyu; Song, Xiuxian; Tan, Q.; Wu, Liang-Kai

doi:10.1016/j.joi.2023.101421

Cited by 2 publications

(1 citation statement)

References 51 publications

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“…Huang et al [18] analyzed hot topics concerning technology and content evolution in patents related to carbon capture, utilization, and storage technology using the LDA model. Ye et al [19] used the LDA model to identify research topics and built mapping relationships on topics to both help fund projects and identify cross-domain categories; also, the evolution of research topics was analyzed. Zhang and Sun [20] analyzed the subjects' interdisciplinary characteristics and constructed a measurement index system, and then identified interdisciplinary subjects with the help of the PhraseLDA model.…”

Section: Recognition Methods Based On Content Miningmentioning

confidence: 99%

Research Frontiers in the Field of Agricultural Resources and the Environment

Chuan,

Zhao,

et al. 2024

Applied Sciences

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From the perspective of project and paper datasets, research frontier recognition in the field of agricultural resources and the environment using the Latent Dirichlet Allocation (LDA) topic extraction model was studied. By combining the wisdom of domain experts to judge the similarities and differences of clustering topics between the two data sources, multidimensional indicators, such as the emerging degree, attention degree, innovation degree, and intersection degree, were comprehensively constructed for frontier identification. The methods for hot research frontiers, emerging research frontiers, extinction research frontiers, and potential research frontiers were proposed. The empirical research in the field of agricultural resources and the environment showed that the “interaction mechanism of plant–rhizosphere–microbial diversity” was a hot research frontier in the years 2016–2021. The themes of “wastewater treatment technology and efficient utilization of water resources”, the “value-added utilization of agricultural wastes and sustainable development”, the “soil ecological response mechanism under agronomic management measures”, and the “mechanism of soil landslide, erosion, degradation and prediction evaluation” were judged as potential research frontiers. The theme of “ecosystems management and pollution control of agricultural and animal husbandry” was recognized as an emerging research frontier. The results confirm that the fusion method of extracting topics from project and paper data, combined with expert intelligence and frontier indicators for fine classification of frontiers, is an optional approach. This study provides strong support for accurately identifying the forefront of scientific research, grasping the latest research progress, efficiently allocating scientific and technological resources, and promoting technological innovation.

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Section: Recognition Methods Based On Content Miningmentioning

confidence: 99%