文献类型： 会议论文
第一作者： Ferenc Tolner
作者： Ferenc Tolner 1 ; Balázs Barta 2 ; Gy?rgy Eigner 3 ;
作者机构： 1.Pannon Business Network Association, Szombathely, Hungary|óbuda University Doctoral School of Applied Informatics and Applied Mathematics, Budapest, Hungary
2.Pannon Business Network Association, Szombathely, Hungary
3.University Research and Innovation Center, Physiological Controls Research Center, óbuda University|Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, óbuda University
关键词： Social networking (online);Collaboration;Complex networks;Time measurement;Resource management;Informatics;Knowledge transfer
会议名称： IEEE International Symposium on Computational Intelligence and Informatics
主办单位：
页码： 185-190
摘要： Complex networks can often be characterized by a fundamental structure that can be described by general principles. The same holds for social networks of partnership formations. Connections arose from the H2020 R& D funding program can also be analysed this way that is hugely affected by endogenous impacts. Nevertheless, self-organization occurs naturally that results high preferential points, near scale-free connection-network and significant inequalities among partners, EU member states and regions. Albeit the goal of such programs is not to increase regional cohesion but to remove obstacles from a borderless knowledge transfer, the two fields are not sharply separable. The aim of the present study is to shed light on regional connections within the H2020 social network and its time evolution via investigation of graph centrality measures. Since long-term regional development also necessitates strategical thinking regarding resource allocation on innovative fields, results could also be utilized by corresponding policymakers.
分类号： tp3
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