论合著网络的结构共同体与社会学术共同体的关系
On the relationship between the structural and socioacademic communities of a coauthorship network
摘要：
本文提出了一项研究，比较检测到的结构社区的合著网络组成的网络的学者的社会学术特征。合作网络是从一个多机构，跨学科的研究小组的书目记录，专注于传感器网络和无线通信的研究。采用四种不同的社区发现算法为网络中的每个学者分配一个结构社区：领先特征向量，walktrap，边缘介数和spinglass。社会学术特征是从学者中收集的，包括他们的学术部门，学术联系，原籍国和学术地位等信息。皮尔森的$χ^2$测试，与模拟蒙特卡洛，揭示了结构社区最好的代表在同一学术部门和同一机构工作的个人群体。这一结果的概括表明，即使在跨学科，多机构的研究小组，合著主要是由部门和机构的联系。
英文摘要：
This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic record of a multi-institution, interdisciplinary research group focused on the study of sensor networks and wireless communication. Four different community detection algorithms were employed to assign a structural community to each scholar in the network: leading eigenvector, walktrap, edge betweenness and spinglass. Socioacademic characteristics were gathered from the scholars and include such information as their academic department, academic affiliation, country of origin, and academic position. A Pearson's $χ^2$ test, with a simulated Monte Carlo, revealed that structural communities best represent groupings of individuals working in the same academic department and at the same institution. A generalization of this result suggests that, even in interdisciplinary, multi-institutional research groups, coauthorship is primarily driven by departmental and institutional affiliation.
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