摘要
[目的/意义]从知识流动的角度,探究世界城市学科的学术影响力,为后续城市学科研究及投入产出模型的应用提供参考。[方法/过程]以物理学科为例,基于美国物理学会(APS)期刊论文数据集及其自有的物理学与天文学分类方案(PACS),构建城市物理学子领域分类体系及知识流网络,考察城市科研产出分布情况,并借助投入产出模型衡量城市物理学子领域的影响力,最后将影响力排序列表与PageRank、HITS算法所得排序列表比较,讨论不同算法特性对排序列表的影响。[局限]受限于数据的可得性,缺乏对宏观学科以及最新数据的分析。[结果/结论]研究发现:(1)城市在物理领域的科研产出存在较大异质性,整体服从幂律分布,且高科研产出城市主要位于欧洲、北美洲和东亚地区,其中东亚地区主要为日本和中国;(2)城市内部各物理学子领域间影响力差异显著,USA-Cambridge的基本粒子物理和场(10)子领域学术影响力排名第一;(3)投入产出模型综合考虑了引用的数量和质量,且算法复杂度较低,对引用结构的敏感性要低于PageRank和HITS算法,为评价城市学科学术影响力提供了新的可靠分析范式。
[Objective/Significance] From the perspective of knowledge flow, this study explores the influence of the world urban discipline and provides a reference for the subsequent research in the urban discipline and the application of the input-output model. [Methods/Processes] Taking physics as an example, based on the American Physical Society(APS) journal paper dataset and its own Physics and Astronomy Classification Scheme(PACS), this article constructs a classification system and knowledge flow network for urban physics subfields, examines the distribution of urban research output, and measures the influence of urban physics subfields with the help of input-output models. Finally, the impact ranking list is compared with the ranking list obtained from PageRank and HITS algorithms, and the effects of different algorithm characteristics on the ranking list are discussed. [Limitations] Limited by the availability of data, there is a lack of analysis of macro disciplines and the latest data. [Results/Conclusions] The results show that:(1) There is a large heterogeneity in scientific research output of cities in the field of physics, and the overall obeys a power-law distribution, and the cities with high scientific research output are mainly located in Europe, North America and East Asia, of which East Asia is mainly Japan and China;(2) The influence of various physics subfields within cities varies significantly, and the academic influence of elementary particle physics and field(10) in Cambridge, USA ranks first;(3) The input-output model integrates the quantity and quality of citations, and the algorithm is less complex and less sensitive to the citation structure than the PageRank and HITS algorithms, providing a new and reliable analytical paradigm for measuring the influence of urban discipline.
作者
郭金忠
王申宏
刘晓玲
冯贺禾
GUO Jinzhong;WANG Shenhong;LIU Xiaoling;FENG Hehe(School of Information Management,Xinjiang University of Finance and Economics,Urumqi 830012,China)
出处
《情报工程》
2022年第6期88-102,共15页
Technology Intelligence Engineering
基金
国家自然科学基金项目“科研人员校友网络对高校科研成果转化的影响及机理研究”(NSFC No.72264036)
中国科学院“西部青年学者”项目“国家科学领域的重要性及相互支撑和影响关系研究”(2020-XBQNXZ-020)
新疆维吾尔自治区高校科研计划项目“科研评估中计量指标与方法的研究”(XJEDU2020Y033)。
关键词
科学计量学
影响力评价
知识流网络
投入产出模型
地理分布
可视化
Scientometrics
impact evaluation
knowledge flow network
input-output model
geographic distribution
visualization