论文标题
学术期刊的相似性网络融合
Similarity network fusion for scholarly journals
论文作者
论文摘要
本文通过使用网络融合技术探讨了学术期刊之间的智力和社会邻近性。期刊之间的相似性最初是通过基于共同提示,共同作者和共同编辑者的三层网络来表示的。然后,通过构建融合相似性网络将三层中包含的信息结合在一起。融合包括一个无监督的过程,该过程利用了层的结构特性。随后,采用了部分距离相关性来测量每一层对融合网络结构的贡献。最后,通过使用模块化探索了融合网络的社区形态。在考虑的三个领域(即经济学,信息和图书馆科学和统计)中,对融合网络结构的主要贡献是由编辑产生的。该结果表明,编辑作为期刊的守门人的作用在定义学术社区的边界方面最相关。在信息和图书馆科学和统计学中,期刊的簇反映了子场的专业知识。在经济学中,根据替代方法学方法,期刊似乎可以更好地解释。因此,代表融合网络中期刊集群的图形是探索研究领域的强大工具。
This paper explores intellectual and social proximity among scholarly journals by using network fusion techniques. Similarities among journals are initially represented by means of a three-layer network based on co-citations, common authors and common editors. The information contained in the three layers is then combined by building a fused similarity network. The fusion consists in an unsupervised process that exploits the structural properties of the layers. Subsequently, partial distance correlations are adopted for measuring the contribution of each layer to the structure of the fused network. Finally, the community morphology of the fused network is explored by using modularity. In the three fields considered (i.e. economics, information and library sciences and statistics) the major contribution to the structure of the fused network arises from editors. This result suggests that the role of editors as gatekeepers of journals is the most relevant in defining the boundaries of scholarly communities. In information and library sciences and statistics, the clusters of journals reflect sub-field specializations. In economics, clusters of journals appear to be better interpreted in terms of alternative methodological approaches. Thus, the graphs representing the clusters of journals in the fused network are powerful instruments for exploring research fields.