  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.
