  The fractal nature of complex networks has received a great deal of research
interest in the last two decades. Similarly to geometric fractals, the
fractality of networks can also be defined with the so-called box-covering
method. A network is called fractal if the minimum number of boxes needed to
cover the entire network follows a power-law relation with the size of the
boxes. The fractality of networks has been associated with various network
properties throughout the years, for example, disassortativity, repulsion
between hubs, long-range-repulsive correlation, and small edge betweenness
centralities. However, these assertions are usually based on tailor-made
network models and on a small number of real networks, hence their ubiquity is
often disputed.
  Since fractal networks have been shown to have important properties, such as
robustness against intentional attacks, it is in dire need to uncover the
underlying mechanisms causing fractality. Hence, the main goal of this work is
to get a better understanding of the origins of fractality in complex networks.
To this end, we systematically review the previous results on the relationship
between various network characteristics and fractality. Moreover, we perform a
comprehensive analysis of these relations on five network models and a large
number of real-world networks originating from six domains. We clarify which
characteristics are universally present in fractal networks and which features
are just artifacts or coincidences.
