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.
翻译：引文网络可以揭示关于科学发展和不同知识领域之间关系的许多重要信息,因此,许多研究分析了这类网络的地形特性,经常利用从一组相关关键词或查询中获得的物品建立引文网络,在这里,我们研究引用网络对于收集相关文章所使用的关键词的稳健性,提议了一种扰动方法,即对缺失的关键词对引文网络的地形学和社区结构的影响进行量化,此外,关键词与引用网络社区结构之间的关系利用一个简单模型产生的网络进行研究,我们发现,由于其高度模块化的结构,即使许多相关关键词被遗漏,引用网络的社区结构也往往得到维护,此外,拟议的模式可以反映缺失的关键词对不同情况的影响。
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