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I am very new to social network analysis and working on a project here that I am not sure what's possible to model.

I don't want to quite call this multi-level because I am not exactly looking at variability over multiple levels (although maybe I am), but here is what I am interested in. The exact context here is community health workers who put on programs in their community with the help of local non-profits.

I want to see what kinds of networks between non-profits are built by the community health workers. For example, maybe there has never been collaboration before between two non-profits and that has changed due to the effort of the health worker.

It's a silly example but this is the type of data I would think I would want to collect -- individuals and the entities they worked with.

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After that, I am not sure how I would model this as I'm interested in a network of organizations as "connected" by individuals.

Like I said I am new to this area so if I'm overlooking something, not explaining this well or just all wet, let me know! Thank you.

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If I understand your data and setup correctly, you have what is called a bipartite graph (or bipartite network). This kind of network is defined by the following properties:

  • There are two types of nodes. Here, the types are health workers and organisations.

  • Every edge connects a node of one type with a node of the other type. Here, all edges connect a heath worker to an organisation. There are not edges connecting one health worker to another or one organisation to another.

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  • $\begingroup$ Yes, this makes a lot of sense. Thanks so much for pointing me in the right direction. $\endgroup$ – georgem Mar 27 at 12:10

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