On the stability of citation networks

Citation networks can reveal important information regarding the development of science and the relationship between different areas of knowledge. Frequently, citation networks are created using articles acquired from a set of relevant keywords or queries. Here, we study the robustness of citation networks communities 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 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. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

Citation networks can provide valuable insights into the development of science and the connections between different knowledge areas. This study examines the robustness of citation network communities in relation to the keywords used to collect relevant articles. The findings show that the structure of citation network communities tends to remain intact even when certain keywords are absent, thanks to their highly modular nature. Additionally, a simple model is used to explore the relationship between keywords and the community structure, while also capturing the impact of missing keywords in different scenarios.