作者潜在跨学科合作度模型构建与合作组合识别——以图书情报学与计算机学科为例

发布时间：2018-08-25 13:09

【摘要】：[目的/意义]跨学科合作不仅能够促进科研工作的开展,更能够促进学科的发展。因此,文章通过定量计算作者间的潜在跨学科合作度指数,识别潜在合作组合,为学科间作者的交流合作提供参考。[方法/过程]构建作者潜在跨学科合作度指数模型;以图书情报学与计算机学科为例,选择综合学科扩散指标较高的期刊为数据来源,在CNKI数据库检索2011—2015年间相应期刊的文献信息;运用VBA语句抽取两学科的交叉研究主题,计算各个主题的两学科作者间潜在跨学科合作度,并识别潜在跨学科合作组合。[结果/结论]研究发现社会网络、大数据、数据挖掘等主题词是图书情报学与计算机学科的主要交叉研究主题,并识别出各主题的高潜在合作度作者组合,这一结论为研究人员寻求跨学科合作对象提供了一定的参考。
[Abstract]:[Objective/Significance] Interdisciplinary cooperation can not only promote the development of scientific research, but also promote the development of disciplines. Therefore, this paper identifies potential cooperation combinations by quantitatively calculating the potential interdisciplinary cooperation index among authors, and provides a reference for the exchange and cooperation of interdisciplinary authors. The index model, Taking Library and information science and computer science as an example, selects periodicals with high diffusion index of comprehensive subjects as data sources, searches the literature information of corresponding periodicals from 2011 to 2015 in CNKI database, extracts the interdisciplinary research topics of two disciplines by using VBA sentences, and calculates the potential interdisciplinary cooperation degree between authors of each subject. RESULTS/CONCLUSIONS The research found that social networks, large data, data mining and other subject terms were the main cross-cutting research topics of Library and information science and computer science, and identified the high potential collaborative degree authors of each subject. This conclusion provided a basis for researchers to seek interdisciplinary collaborative subjects. Fixed reference.
【作者单位】：山东理工大学科技信息研究所;
【基金】：国家社会科学基金项目“基于量化与质性数据的跨学科合作行为研究”的成果之一,项目编号:16BTQ078
【分类号】：G353.1

【参考文献】