Social systems are emergent complex systems, and can be described with system analysis and in he language of complex systems and graphs.
For example, I quote from here
In order to understand how societies can be modelled by systems theory
it is instructive to look at some simple examples. In feudal Europe
the organisation of society was exceptionally hierarchical. This is
modeled in systems theory by a sort of control graph, which is a tree,
with the lord at the top and his immediate vassals below him. In this
structure it was possible to approximate, in many circumstances,
control over a group of people with control over the leader of the
hierarchy. This has a large number of consequences.
If the behaviour of the system can be modeled by behaviour of the
lord, then the system can not act in ways more complex than the lord.
Because of this, the system remains simple. It also means that the
system can easily act coherently. It is capable of leading armies, and
interacting with other feudal states in simple ways.
In reality no perfect control hierarchies exist. There will always be
lateral control links, various types of conspiratorial actions etc.
However, for feudalism this model often remains a good
approximation.As we move through history to early capitalism we start
seeing a move towards more “hybrid” models of control, where many more
lateral links exist and the system takes on the possibility of
evolving more decentralised, more complex behaviours. In addition, it
becomes less brittle. One might conjecture that feudalism was in some
sense doomed when capitalism arose because the environment of
interaction became too complex. The modern world has moved to a highly
interconnected network-model capitalism. This is almost the antithesis
of feudalism within the framework of the connectivity of the model.It
is important to note a few things about the network model. Networks
can have vary different internal structure. A large amount of
interconnectedness does not rule out particular internal patterns, in
fact we know that many complex systems, including social networks,
don’t have “random” graph structures. This internal structure can have
big effects on emergent behaviour. All networks are not the same.*
So what this is suggesting is to draw a picture showing the relations between your social entities. Each person can be one node, but a corporation or a family is a collection of nodes. You can also have non animate things like religious symbols or buildings as nodes. Look at how complex what you have drawn is. Are there missing links between nodes that plausibly ought to be there?
Any pattern of regularity, or clusters of highly connected nodes have the potential to be identified as the next layer up in the various layers of a complex system (which is generally always a pyramid with the emergent and more highly complex behaviours on top of a lower complexity layer below it.
The feedbacks between the entities and levels of hierarchy in the overall system characterise you social structure.
There are general 'rules' that apply to all complex systems whether we are talking about a human economy or a weather system. Even a convection current in a room of your house qualifies.