Expanding the boundaries of interdisciplinary field: Contribution of Network Science journal to the development of network science

IF 1.4 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY
Valentina V. Kuskova, Dmitry G. Zaytsev, Gregory S. Khvatsky, Anna A. Sokol, Maria D. Vorobeva, Rustam A. Kamalov
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引用次数: 0

Abstract

Abstract In this paper, we examine the contribution of Network Science journal to the network science discipline. We do so from two perspectives. First, expanding the existing taxonomy of article contribution, we examine trends in theory testing, theory building, and new method development within the journal’s articles. We find that the journal demands a high level of theoretical contribution and methodological rigor. High levels of theoretical and methodological contribution become significant predictors of article citation rates. Second, we look at the composition of the studies in Network Science and determine that the journal has already established a solid “hard core” for the new discipline.
拓展跨学科领域的边界——网络科学期刊对网络科学发展的贡献
摘要本文考察了《网络科学》杂志对网络科学学科的贡献。我们从两个角度这样做。首先,扩展现有的文章贡献分类,我们考察了期刊文章中理论测试、理论构建和新方法发展的趋势。我们发现,该期刊需要高水平的理论贡献和方法严谨性。高水平的理论和方法学贡献成为文章引用率的重要预测因素。其次,我们查看了《网络科学》的研究组成,并确定该杂志已经为新学科建立了坚实的“核心”。
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来源期刊
Network Science
Network Science SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
3.50
自引率
5.90%
发文量
24
期刊介绍: Network Science is an important journal for an important discipline - one using the network paradigm, focusing on actors and relational linkages, to inform research, methodology, and applications from many fields across the natural, social, engineering and informational sciences. Given growing understanding of the interconnectedness and globalization of the world, network methods are an increasingly recognized way to research aspects of modern society along with the individuals, organizations, and other actors within it. The discipline is ready for a comprehensive journal, open to papers from all relevant areas. Network Science is a defining work, shaping this discipline. The journal welcomes contributions from researchers in all areas working on network theory, methods, and data.
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