  Citation networks emerge from a number of different social systems, such as
academia (from published papers), business (through patents) and law (through
legal judgements). A citation represents a transfer of information, and so
studying the structure of the citation network will help us understand how
knowledge is passed on. What distinguishes citation networks from other
networks is time; documents can only cite older documents. We propose that
existing network measures do not take account of the strong constraint imposed
by time. We will illustrate our approach with two types of causally aware
analysis. We apply our methods to the citation networks formed by academic
papers on the arXiv, to US patents and to US Supreme Court judgements. We show
that our tools can reveal that citation networks which appear to have very
similar structure by standard network measures turn out to have significantly
different properties. We interpret our results as indicating that many papers
in a bibliography were not directly relevant to the work and that we can
provide a simple indicator of the important citations. We suggest our methods
may highlight papers which are of more interest for interdisciplinary research.
We also quantify differences in the diversity of research directions of
different fields.
