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Comparative analysis of university-governmententerprise co-authorship networks in three scientific domains in the region of Madrid

机译:马德里地区三大科学领域的大学 - 企业共同创作网络比较分析

摘要

Introduction: In an economy geared to innovation and competitiveness in research and development activities, inter-relationships between the university, private enterprise and government are of considerable interest. Networking constitutes a priority strategy to attain this strategic objective and a tool in knowledge-based economies.Method: Drawing from a full inventory of co-authored scientific articles, collaborating networks are defined and analysed with the social network analysis method, using Pajek software and graphedwith the Kamada-Kawai algorithm for visualization.Analysis: Scientific production involving intraregional collaboration in the Madrid region is analysed across three subject categories. The data used were taken from the Web of Science for the years 1995-2003. The main indicators of social networking obtained were: density average degree, normalized degree and degree centralization, betweenness centralization, closeness centralization and clustering coefficient.Results: Networking led to a moderate rise in the number of links and participating actors, with more Spanish companies and multi-national subsidiaries in the second period. The largest number of linkswas recorded for public universities located in the Community of Madrid.Conclusions: The data resulting from the social network analysis conducted provided insight into the structural characteristics of the networks generated and their evolution. The visualization methodology used proved to be highly informative for identifying not only the main actors, but clusters and components as well. The analysis afforded a useful perspective for understanding the dynamics of collaborating networks.
机译:简介:在一个致力于创新和研发活动竞争力的经济中,大学,私营企业和政府之间的相互关系备受关注。网络化是实现这一战略目标的优先战略,也是知识型经济中的一种工具。方法:从完整合着的科学论文清单中,使用社交网络分析方法使用Pajek软件定义和分析协作网络。分析:使用马德里地区的区域内合作进行科学生产的三个主题类别的分析。使用的数据来自1995-2003年的Web of Science。获得的社交网络的主要指标是:密度平均程度,归一化程度和程度集中度,中间度集中度,亲密度集中度和聚类系数。结果:网络导致链接和参与者的数量适度增加,西班牙公司和第二阶段是跨国子公司。记录最多的是位于马德里自治区的公立大学的链接。结论:进行的社交网络分析得出的数据提供了对生成的网络的结构特征及其演变的深入了解。事实证明,所使用的可视化方法不仅对识别主要参与者,而且对集群和组件也具有很高的参考价值。该分析为理解协作网络的动态提供了有用的视角。

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