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I am trying to solve the following problem: I have relationship data
collected at various points in time regarding the participation of different
members in a discussion group. Data were accumulated periodically, so the
network at time T+1 consists of the mapping of all discussions that have
occurred in the period between T and T+1. The data are in the form of
adjacency matrices. I need to compare the networks that existed at different
What are some of the ways to compare the network structure at T with that at
T+1? I am thinking of calculating individual-level statistics such as
various types of centrality (degree, closeness etc.) for each actor in the
network at both T and T+1 and see how the statistics have changed. Is this
approach correct? In addition, I will also compare network-level
statistics such as centralization of the network at different time periods.
Should I include all the actors in both matrices, even though some of them
have not contributed to the discussion at either T or T+1? Or, should the
adjacency matrices for specific times include only those actors that have
contributed? What the relative merits and demerits of these two types of
representations? What are some good references to which I may refer? BTW,
I am using the SNA library in R for my computations.
Any advice is much appreciated.
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