  Large knowledge graphs combine human knowledge garnered from projects ranging
from academia and institutions to enterprises and crowdsourcing. Within such
graphs, each relationship between two nodes represents a basic fact involving
these two entities. The diversity of the semantics of relationships constitutes
the richness of knowledge graphs, leading to the emergence of singular
topologies, sometimes chaotic in appearance. However, this complex
characteristic can be modeled in a simple way by introducing the concept of
superficiality, which controls the overlap between relationships whose facts
are generated independently. With this model, superficiality also regulates the
balance of the global distribution of knowledge by determining the proportion
of misdescribed entities. This is the first model for the structure and
dynamics of knowledge graphs. It leads to a better understanding of formal
knowledge acquisition and organization.
