He Chaocheng, Wu Jiang, Zhang Qingpeng
School of Information Management, Wuhan University, Wuhan, Hubei China.
School of Data Science, City University of Hong Kong, Kowloon, Hong Kong, China.
Scientometrics. 2021;126(5):4005-4037. doi: 10.1007/s11192-021-03943-w. Epub 2021 Mar 20.
Research collaborations, especially long-distance and international collaborations, have become increasingly prevalent worldwide. Recent studies highlighted the significant role of research leadership in collaborations. However, existing measures of the research leadership do not take into account the intensity of leadership in the co-authorship network. More importantly, the spatial features, which influence the collaboration patterns and research outcomes, have not been incorporated in measuring the research leadership. To fill the gap, we construct an institution-level weighted co-authorship network that integrates two types of weight on the edges: the intensity of collaborations and the spatial score (the geographical distance adjusted by the cross-linguistic-border nature). Based on this network, we propose a novel metric, namely the spatial research leadership rank, to identify the leading institutions while considering both the collaboration intensity and the spatial features. The leadership of an institution is measured by the following three criteria: (a) the institution frequently plays the corresponding rule in papers with other institutions; (b) the institution frequently plays the corresponding rule in longer distance and even cross-linguistic-border collaborations; (c) the participating institutions led by the institution have high leadership status themselves. Harnessing a dataset of 323,146 journal publications in pharmaceutical sciences during 2010-2018, we perform a comprehensive analysis of the geographical distribution and dynamic patterns of research leadership flows at the institution level. The results demonstrate that the SpatialLeaderRank outperforms baseline metrics in predicting the scholarly impact of institutions. And the result remains robust in the field of Information Science and Library Science.
The online version contains supplementary material available at 10.1007/s11192-021-03943-w.
研究合作，尤其是远距离和国际合作，在全球范围内日益普遍。最近的研究强调了研究领导力在合作中的重要作用。然而，现有的研究领导力衡量方法没有考虑共同作者网络中领导力的强度。更重要的是，影响合作模式和研究成果的空间特征在衡量研究领导力时并未被纳入。为了填补这一空白，我们构建了一个机构层面的加权共同作者网络，该网络在边的权重上整合了两种类型：合作强度和空间得分（根据跨语言边界性质调整的地理距离）。基于这个网络，我们提出了一种新的指标，即空间研究领导力排名，以在考虑合作强度和空间特征的同时识别领先机构。一个机构的领导力通过以下三个标准来衡量：（a）该机构在与其他机构合作的论文中经常扮演相应角色；（b）该机构在远距离甚至跨语言边界合作中经常扮演相应角色；（c）由该机构领导的参与机构本身具有较高的领导力地位。利用2010 - 2018年期间323,146篇药学领域期刊出版物的数据集，我们对机构层面研究领导力流动的地理分布和动态模式进行了全面分析。结果表明，空间领导者排名在预测机构的学术影响力方面优于基线指标。并且在信息科学与图书馆学领域，该结果仍然稳健。
在线版本包含可在10.1007/s11192 - 021 - 03943 - w获取的补充材料。
