Co-authorship networks, where nodes represent authors and edges represent co-authorship relations, are key to understanding the production and diffusion of knowledge in academia. Social constructs, biases (implicit and explicit), and constraints (e.g. spatial, temporal) affect who works with whom and cause co-authorship networks to organise into tight communities with different levels of segregation. We aim to look at aspects of the co-authorship network structure that lead to segregation and its impact on scientific production. We measure segregation using the Spectral Segregation Index (SSI) and find 4 ordered segregation categories: completely segregated, highly segregated, moderately segregated and non-segregated communities. We direct our attention to the non-segregated and highly segregated communities, quantifying and comparing their structural topologies and k-core positions. When considering communities of both categories (controlling for size), our results show no differences in density and clustering but substantial variability in core position. Larger non-segregated communities are more likely to occupy cores near the network nucleus, while the highly segregated ones tend to be closer to the network periphery. Finally, we analyse differences in citations gained by researchers within communities showing different segregation categories. Researchers in highly segregated communities get more citations from their community members in middle cores and gain more citations per publication in middle/periphery cores. Those in non-segregated communities get more citations per publication in the nucleus. To our knowledge, this work is the first to characterise community segregation in co-authorship networks and investigate the relationship between community segregation and author citations.
The specific shapes of gender imbalance in scientific authorships: a network approach
与妇女在学术界和研究中日益增长的重要性相比，合作研究中的性别差异很少受到关注。毫不奇怪，大多数文献计量数据库都严重缺乏按性别分列的直接可用信息。虽然基于拓扑的网络方法经常被用于研究合作，性别差异对拓扑结果的影响的研究仍然很少。在这里，网络的科学主题是用来表征模式，可能与五类作者的基础上建立的性别。我们发现足够的证据表明，科学作者的性别不平衡给网络带来了一个特殊的特征，这些网络是由2010-2015年期间在Web of Science（WoS）索引的经济学期刊上发表的论文引起的，并且至少有一位作者隶属于葡萄牙机构。我们的研究结果表明，出现了一个特定的模式时，网络的共同出现的主题是从一组专为男性撰写的文件。这种男性独占的作者身份条件被认为是网络结构中出现这种特定形状的唯一原因。这种独特的特点可能有助于未来的网络分析的研究合作和跨学科。
Research networks generated by organizational structures, co-authorships and citations: A Case Study of German Centre for Integrative Biodiversity Research (iDiv)
Forecasting Faculty Placement from Patterns in Co-authorship Networks
Khoury College of Computer Sciences, Northeastern University（诺思韦普大学科里学院）；Network Science Institute, Northeastern University（网络科学研究所）；Santa Fe Institute（圣菲研究所）
Systematic comparison of gender inequality in scientific rankings across disciplines
University of Exeter（埃克塞特大学）；Complexity Science Hub Vienna（维也纳复杂科学中心）；Technische Universität Graz（格拉茨工业大学）；Constructor University（康斯特鲁克托大学）；Northeastern University London（伦敦东北大学）；Khoury College of Computer Sciences, Northeastern University（东北大学凯利计算机科学学院）；Center for Collective Learning, Corvinus Institute for Advanced Studies at Corvinus University of Budapest（布达佩斯科维纽斯大学高级研究所集体学习中心）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）；Federal University of Ceará（塞阿拉联邦大学）
