From Weak Ties to Strong Ties: Community vs. Social Networks 3

Hello Carolyn,

Thank you for commenting.

I am not 100% sure if I get your point. But my understanding of the situation you described can be sufficiently analyzed simply by social network analysis (SNA). Using SNA you will be identified as a bridge (or connector, boundary spanner, hidden influencers, etc) between the multiple communities. That is, if we compute the betweenness centrality using SNA, you will have extraordinarily high value for this SNA metric. I've written about an example of such analysis in an earlier post "Social Network Insights from Unconventional Graph Metrics."

The time dimension is a characteristics distinction between Dynamic network analysis (DNA) and SNA, because all DNA applications deal with changes of the network over time. That is why it is called Dynamic. However, not all problems required the temporal dimension to reach a good solution. So DNA is often not used because most of the time SNA is sufficient. Just as Einstein's Relativity is rarely used for problems we encounter on earth, because Newtonian Mechanics are plenty sufficient for that, even though Relativity is a much more complete theory and much more powerful.

DNA as opposed to SNA will show its superior strength when dealing with complex network systems where the entities (the nodes and vertices in a graph) and relationships (edges in a graph) can both change over time. An example of change of relationship is when two person were friends today, but become enemies tomorrow. An example of change of entities is where a person change from being healthy to being infected. Another example would be if a caterpillar metamorephosed into a butterfly. As you can see in my examples, DNA is used frequently in conflict and resolution studies and their simulations, as well as disease propagation models in epidemiology, or animal population dynamics in ecology.

So having multiple communities interacting with each other or with actors mediating the interactions between them would probably not be considered as a kind of DNA. Nevertheless, you have posed a very interesting SNA problem that I've recently analyzed. If this subject interests you, I highly recommend that you take a look at "Social Network Insights from Unconventional Graph Metrics." The discussion following that post may also be interesting to you, if my memory still serves me well.  :)