Literature reviews are required at early stages of a traditional research progression. Many systematic approaches help researchers identify relevant literature. However, there is far less support for interpreting large collections of references. Understanding the evolution of knowledge within a discipline requires an awareness of the collaborative networks from which significant advances originate. Unfortunately, this relational awareness is only acquired after years of professional experience. Therefore, early-career researchers are at a fundamental disadvantage when conducting literature reviews. Social Network Analysis (SNA) can make the interpretation of large collections of literature more manageable. This paper provides a method for generating a co-authorship network from reference lists. The partition of the co-authorship network into communities provides a reviewer with direction to organise literature into meaningful groups. The interpretation of seemingly disparate and entangled research programs is far more manageable when interpreting smaller collections of highly relevant literature.