科学数据引用网络建模及演化特征分析OA北大核心CHSSCDCSSCICSTPCD
Modeling and Evolution Analysis of Scientific Data Citation Network
[目的/意义]将社会网络分析方法应用于科学数据引用特征及规律研究,可以直观呈现出数据引用的复杂网络结构,挖掘数据引用更深层次的价值.[方法/过程]通过辨析科学数据引用特征,构建GEO数据共被引网络模型,并对网络的整体演化、核心个体、社区结构等进行分析.[结果/结论]研究结果表明,GEO数据共被引网络的度和度分布空间差异明显,平均路径长度较短且聚集系数较大,网络中核心个体优势明显,社区结构稳定且特征突出,社区间联系逐渐增强.
[Purpose/Significance]The study applies the social network analysis method to the research on the char-acteristics and laws of scientific data citations can intuitively present the complex network structure of data citations,and taps the deeper value of data citations.[Method/Process]The study constructed a GEO data co-citation network model by analyzing the citation characteristics of scientific data,and analyzed the overall evolution of the network,core individuals,and community structures.[Result/conclusion]The research results show that the degree and degree distribution space of the GEO data co-citation network are significantly different,the average path length is shorter and the aggregation coeffi-cient is larger,the core individual advantages in the network are obvious,the community structure is stable and the charac-teristics are prominent,and the community The connection between them is gradually strengthened.
杨宁;张志强;黄飞虎;张鑫
中国科学院成都文献情报中心, 四川 成都 610041||中国科学院大学经济与管理学院信息资源管理系, 北京 100190四川大学计算机学院, 四川 成都 610065
科学数据数据引用网络建模结构特征
scientific datadata citationnetwork modelingstructural features
《现代情报》 2024 (005)
45-57 / 13
中国科学院文献情报能力建设专项项目"支撑院党组决策的战略情报感知平台建设与应用"(项目编号:292021000479);ISTIC-CLARIVATE ANALYTICS科学计量学联合实验室开放基金项目"引文视角下科学数据出版及使用现状研究——以高能物理领域为例"(项目编号:IT2214).
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