Citation networks can reveal many important information regarding the development of science and the relationship between different areas of knowledge. Thus, many studies have analyzed the topological properties of such networks. Frequently, citation networks are created using articles acquired from a set of relevant keywords or queries. Here, we study the robustness of citation networks with regards to the keywords that were used for collecting the respective articles. A perturbation approach is proposed, in which the influence of missing keywords on the topology and community structure of citation networks is quantified. In addition, the relationship between keywords and the community structure of citation networks is studied using networks generated from a simple model. We find that, owing to its highly modular structure, the community structure of citation networks tends to be preserved even when many relevant keywords are left out. Furthermore, the proposed model can reflect the impact of missing keywords on different situations.

中文翻译：

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论引文网络的稳定性

引文网络可以揭示有关科学发展以及不同知识领域之间关系的许多重要信息。因此，许多研究已经分析了这种网络的拓扑特性。通常，引用网络是使用从一组相关关键字或查询中获取的文章来创建的。在这里，我们针对用于收集相应文章的关键字研究了引文网络的鲁棒性。提出了一种摄动方法，在该方法中量化了关键词丢失对引文网络拓扑和社区结构的影响。此外，还使用从简单模型生成的网络来研究关键字与引文网络的社区结构之间的关系。我们发现，由于其高度模块化的结构，即使遗漏了许多相关的关键字，引文网络的社区结构也倾向于保留下来。此外，提出的模型可以反映缺失关键字对不同情况的影响。