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Similarity network fusion for scholarly journals
arXiv - CS - Digital Libraries Pub Date : 2020-11-13 , DOI: arxiv-2011.06795
Federica Baccini, Lucio Barabesi, Alberto Baccini, Mahdi Khelfaoui, Yves Gingras

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 combined by implementing a fused similarity network. 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. As to information and library sciences and statistics, the clusters of journals reflect sub-field specializations. As to 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 explorative instruments for exploring research fields.

中文翻译:

学术期刊的相似网络融合

本文通过使用网络融合技术探索学术期刊之间的智力和社会接近度。期刊之间的相似性最初是通过基于共同引用、共同作者和共同编辑的三层网络来表示的。三层中包含的信息通过实现融合相似性网络进行组合。随后,采用部分距离相关性来衡量每一层对融合网络结构的贡献。最后,通过使用模块化来探索融合网络的社区形态。在所考虑的三个领域(即经济学、信息学、图书馆学和统计学)中,对融合网络结构的主要贡献来自编辑。这一结果表明,编辑作为期刊看门人的角色与界定学术社区的界限最为相关。至于信息和图书馆科学和统计,期刊集群反映了子领域的专业化。至于经济学,从替代方法论的角度来看,期刊集群似乎可以得到更好的解释。因此,表示融合网络中期刊集群的图是探索研究领域的强大探索工具。
更新日期:2020-11-16
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