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Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research
Scientometrics ( IF 3.9 ) Pub Date : 2021-03-20 , DOI: 10.1007/s11192-021-03922-1
Tobias Koopmann , Maximilian Stubbemann , Matthias Kapa , Michael Paris , Guido Buenstorf , Tom Hanika , Andreas Hotho , Robert Jäschke , Gerd Stumme

Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity.



中文翻译:

邻近维度和协作的出现:有关德国AI研究的HypTrails研究

知识的创造和交流取决于合作。最近的工作表明,协作的出现经常取决于地理位置。但是,共处一处往往会与其他接近度相关联,例如社会纽带或共享的组织环境。为了解决这些因素,已经提出了接近度的多个维度,包括认知,制度,组织,社会和地理上的接近度。由于它们之间密切相关,因此解开这些维度及其对协作的影响是具有挑战性的。为了解决这个问题,我们提出了各种方法来测量不同的接近度。然后,我们提出一种方法,根据它们表示共同发布和共同发明的程度对它们进行比较和排名。我们适应HypTrails方法最初是为解释人类导航而开发的,用于共同创作和共同发明图形。我们在德国研究界的一个子集中,特别是活跃于人工智能(AI)研究的学术作者和发明家,评估了这种方法。我们发现,社交邻近度和认知邻近度对于协作的出现比地理邻近度更为重要。

更新日期:2021-03-21
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