摘要
有组织科研团队建设有赖于对科研合作现象和规律的科学认识。常用于科研合作模式研究的合著者网络默认同一成果的合作者间贡献均等,但这通常与科研合作实践相左。作者贡献声明数据的出现为揭示更细粒度的合作实践提供了重要素材。为此,本研究提出一种利用贡献声明数据构建的新型合作网络——合贡献者网络,为深入研究科研合作问题提供新工具。本研究以PLoS(Public Library of Science)上的药学论文数据为例,以合著者网络为基准,从合贡献者网络的网络结构特征入手,认识此新型合作网络的物理性质;选取当前重要研究方向之一的“合作群体识别”为切入点,进一步认识合贡献者网络的应用价值。研究结果表明:①在网络结构形态上,合贡献者网络比合著者网络更稀疏;②在合作群体识别上,两种网络的群体识别结果部分一致,重合度约为57%;约32%的合作群体在合贡献者网络上发生了重组;③合贡献者网络中的合作群体发文主题比合著者网络更为聚焦,但检验结果并不显著。总体来看,在本研究的数据集上,合贡献者网络较之合著者网络显示出更良好的社区结构;合贡献者网络有助于识别出更细粒度的合作群体,且在所识别的合作群体上发文主题的一致性更高。
The construction of organized scientific research teams relies on a scientific understanding of the phenomena and patterns of research collaboration.The commonly used research model for scientific collaboration,the co-authorship network,assumes equal contributions among co-authors for the same research output,which often contradicts actual re‐search collaboration practices.The emergence of author contribution statement data provides valuable material for reveal‐ing more detailed collaboration practices.This study proposes a novel collaboration network,which is called the“co-con‐tributorship network”and constructed using contribution declaration data,to provide a new tool for investigating scientific collaboration issues in depth.Using article data in the field of medicine from PLoS as an example and the co-authorship network as a baseline,we explore the physical properties of this new collaboration network through its network structure characteristics.Furthermore,we focus on identifying collaboration groups,an essential research direction,to better under‐stand the practical value of the co-contributorship network.The study finds the following:in terms of the network struc‐ture,the co-contributorship network is sparser than the co-authorship network.The results of both networks regarding the identification of collaboration groups partially coincide,with an overlap of approximately 57%.Approximately 32%of the collaboration groups experienced restructuring in the co-contributorship network.The evaluation results show that collabo‐ration groups in the co-contributorship network tend to be more focused on research topics compared to those in the co-au‐thorship network,but the difference is not statistically significant.Overall,based on our dataset,the co-contributorship net‐work exhibits a more favorable community structure compared to the co-authorship network.It helps identify finer-grained collaboration groups with higher consistency in their research topics among the identified groups.
作者
卢超
李梦婷
陈秀娟
董克
魏瑞斌
Lu Chao;Li Mengting;Chen Xiujuan;Dong Ke;Wei Ruibin(Business School,Hohai University,Nanjing 211100;School of Journalism and Communication,Nanjing Normal University,Nanjing 210097;Research Institute for Data Management&Innovation,Nanjing University,Suzhou 215163;Laboratory of Data Intelligence and Interdisciplinary lnnovation,Nanjing University,Nanjing 210023;School of Management Science and Engineering,Anhui University of Finance and Economics,Bengbu 233030)
出处
《情报学报》
CSSCI
CSCD
北大核心
2024年第7期773-788,共16页
Journal of the China Society for Scientific and Technical Information
基金
国家自然科学基金青年科学基金项目“劳动分工视角下科研合作者的科研效能研究”(72004054)
江苏省高等学校基础科学(自然科学)研究面上项目“重大突发公共卫生事件中疫苗研发领域的国际科研合作布局与产出效益研究”(21KJB630008)
中央高校基本科研业务经费专项资金项目“科研团队多样性对科研绩效的因果效应研究”(B220201058)
江苏省社会科学基金后期资助项目“我国NSFC国际合作研究项目国际合作特征与产出规律研究”(21HQ038)。
关键词
科研合作
合著者网络
作者贡献声明
合贡献者网络
scientific collaboration
co-authorship network
author contribution statement
co-contributorship network
