  Due to the fact that the numbers of annually published papers have witnessed
a linear growth in some citation networks, a geometric model is thus proposed
to predict some statistical features of those networks, in which the academic
influence scopes of the papers are denoted through specific geometric areas
related to time and space. In the model, nodes (papers) are uniformly and
randomly sprinkled onto a cluster of circles of the Minkowski space whose
centers are on the time axis. Edges (citations) are linked according to an
influence mechanism which indicates that an existing paper will be cited by a
new paper located in its influence zone. Considering the citations among papers
in different disciplines, an interdisciplinary citation mechanism is added to
the model in which some papers with a small probability of being chosen will
cite some existing papers randomly and uniformly. Different from most existing
models that only study the power-law tail of the in-degree distribution, this
model also characterizes the overall in-degree distribution. Moreover, it
presents the description of some other important statistical characteristics of
real networks, such as in- and out-assortativity, giant component and clear
community structure. Therefore, it is reasonable to believe that a good example
is provided in the paper to study real networks by geometric graphs.
