Finding Scientific Communities In Citation Graphs: Convergent Clustering
arXiv:2007.14452 · doi:10.1162/qss_a_00095
Abstract
Understanding the nature and organization of scientific communities is of broad interest. The `Invisible College' is a historical metaphor for one such type of community and the search for such `colleges' can be framed as the detection and analysis of small groups of scientists working on problems of common interests. Case studies have previously been conducted on individual communities with respect to their scientific and social behavior. In this study, we introduce, a new and scalable community finding approach. Supplemented by expert assessment, we use the convergence of two different clustering methods to select article clusters generated from over two million articles from the field of immunology spanning an eleven year period with relevant cluster quality indicators for evaluation. Finally, we identify author communities defined by these clusters. A sample of the article clusters produced by this pipeline was reviewed by experts, and shows strong thematic relatedness, suggesting that the inferred author communities may represent valid communities of practice. These findings suggest that such convergent approaches may be useful in the future.
References in corpus (9)
- From Louvain to Leiden: guaranteeing well-connected communities
- Which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge?
- Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale
- Increasing trend of scientists to switch between topics
- A small world of citations? The influence of collaboration networks on citation practices
- Clustering scientific publications based on citation relations: A systematic comparison of different methods
- Practical method to reclassify Web of Science articles into unique subject categories and broad disciplines
- Co-citations in context: disciplinary heterogeneity is relevant
- Viewing Computer Science through Citation Analysis; Salton and Bergmark Redux