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  

Potential Interdisciplinary Collaboration Model Construction and Cooperative Combination Identification of Authors

作　　者：李长玲[1] 崔斌[1] 刘小慧[1] 冯志刚[1] 

机构地区：[1]山东理工大学科技信息研究所,山东淄博255049

出　　处：《情报理论与实践》2017年第7期61-66,共6页Information Studies:Theory & Application

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

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。[ Purpose/significance] Interdisciplinary cooperation can promote the development of scientific research as well as the development of disciplines. Therefore, this paper calculates the potential interdisciplinary cooperation degree among authors and identifies the potential cooperation combinations, which can be used as references for interdisciplinary cooperation. [ Method/ process ] The paper constructs a potential interdisciplinary cooperation index model. Taking LIS and the Computer Science as the re- search objects, the paper selects journals with high comprehensive discipline diffusion index as the source journals, and retrieves the literatures of the corresponding journals in CNKI database from 2011 to 2015. The paper uses the VBA sentences to extract the o- verlap topics of the two subjects and calculates the authors＇ potential interdisciplinary cooperation degree, and identifies the poten- tial cooperation combination. [ Result/conclusion] It is found that social network, big data, data mining and other key words are the main cross-subjects of the two disciplines. Moreover, the combinations of authors with high potential cooperation under each top- ic are identified, which provides references for researchers to seek interdisciplinary cooperation.

关 键 词：跨学科 合作度 图书情报学 计算机科学 模型 

分 类 号：G353.1[文化科学—情报学]