基于地理加权合作网络的科研领导力特征研究
Characterizing Research Leadership on Geographical Weighted Collaboration Network
摘要：
研究合作，特别是远距离和跨境合作，在世界范围内越来越普遍。最近的研究强调了研究领导在合作中的重要作用。然而，现有的研究领导的措施没有考虑到领导的合作网络的强度。更重要的是，影响合作模式和研究成果的空间特征，没有被纳入测量的研究领导。为了填补这一空白，我们构建了一个机构级加权合著网络，该网络在边缘上具有两种类型的权重：合作强度和空间得分（由跨境性质调整的地理距离）。基于该网络，我们提出了一种新的度量，即空间研究领导排名（SpatialLeaderRank），以确定领先的机构，同时考虑合作强度和空间特征。利用2010年至2018年期间323，146份药物科学期刊出版物的数据集，我们对机构层面研究领导流的地理分布和动态模式进行了全面分析。结果表明，SpatialLeaderRank在预测机构的学术影响力方面优于基线指标。在情报学和图书馆学领域，这一结果仍然是稳健的。
英文摘要：
Research collaborations, especially long-distance and cross-border 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 has two types of weight on the edges: the intensity of collaborations and the spatial score (the geographic distance adjusted by the cross-border nature). Based on this network, we propose a novel metric, namely the spatial research leadership rank (SpatialLeaderRank), to identify the leading institutions while considering both the collaboration intensity and the spatial features. 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 & Library Science.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
