Social networks, events, entities, actors, actions

There is a fairly substantial body of work that looks at the difference between hierarchical organized groups and network organized groups. The relative merits of each argument fall into a few camps. The hierarchical organization allows for direction of action whereas the network organization requires more direction by intent. When considering networked organization it is important to think about how they are spawned, how they grow, how resilient are they, and what sustains the organization. This is important when thinking about terrorism, cyber warfare, or any conflict where non-state actors may be involved.

This very high overview was written to get down on paper something that might answer a few of those questions.  One goal was to open the idea of the swarm versus network but was passed over in review as that would be to much outside the scope of a blog post.

In considering nation states they are by definition hierarchical controls with “power” (poor choice of words but it will do) derived from the state. The network is the derivation of its own force as hierarchical control does not exist. The nation state is fairly well understood as a political entity. The non-state actor as an entity is less well defined and understood. Part of this is the non-state actor has to exist in a shadow of a nation state such as corporation does, or as a polarity to the nation state as the terrorist (as an example) does.

The analogy of the computer network is often used to describe the non-state actors network. With everything connected to everything else, and hierarchies existing within nodes such as the local area network, campus area network, metropolitan area network existing as hierarchies with redundant and resilient connections. The network analogy though isn’t strong enough to describe all non-state actors and urban campaigners like Hamas. The emerging military operation is a fourth and fifth dimension network.

Most networks are thought of as nodes and connections. You can have three dimensions to actors within that network. The network exists in an x, y, z axis and each edge of a node has some type of connection to another edge. (see figure 1)

A single node can have an entire network below it. Sometimes called super-nodes we might impose hierarchical progression like when we did with our previous example of computer networks. What if the super-node has a node within it that has nodes within it (see figure 2). Like shark teeth that haven’t even grown in yet and discarded as needed? This is a node that is hidden until it is exposed and as such cannot be detected until that exposure. Maybe shark teeth or perhaps children of children of terrorists carrying on the family trade. The generations to follow do not even exist to be diagrammed.

These nodes have connections to nodes that are not connected via any of the primary nodes connections. Consider it like the relationship of a child at school outside of the scope of the parents involvement. The networked nature exists but there is a temporal as well as cognitive dimension in the networked relationships (see figure 3). Consider during the Israel and Hamas conflict that a rocket team moving through a building vertically interacting with residents who never do anything but become casualties afterwards. The residents of such a building may have knowledge of what will transpire but if targeted in retaliation have little in the way of impact on the original rocket teams operational capability.

A primary consideration of the model is thinking about nodes not just as individual actors or entities but, as events. When nodes move from actors to actions/incidents (E) morphing the network changes in the dimensional characteristics. Rather than being our earlier three-dimensional tool it becomes a fourth and fifth dimensional representation. That is a bit beyond my limited intellectual capability or mathematical capability to depict (see figure 4). I believe what is likely occurring is incidents can generate actors through unintended consequences that create incidents. Some would say that this is mixing apples and oranges that events and actors should be separate graphical representations. Unfortunately when dealing with the specifics of conflict that may not be the best way to create an understanding of the relationships. What we are tying to expose it that which is tot covered by a normal network graph. What we end up with is an overlay.

This idea of multi-layered networks and added dimensions answers a few basic questions on the growth of networks. The analogy of playing 3 dimensional chess and having entire new boards suddenly appear with pieces ready to checkmate is the best to answer how this might be a problem.  I’ve tried explaining this idea to people much smarter than me only to be told that it is primarily chaos and as such not describable. Further, I have been told that a depiction is not a description and thus graph theory is not applicable. It would be nice to see if others can consider the real world ramifications and fill in the holes.

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