Hi, all,

I am working on time-series networks. I have one network in each year, and

I totally have 5 networks in 1970, 1980,1990,2000, 2010. Then I use the

layered model to generate communities.

state_G_layers=graph_tool.all.minimize_blockmodel_dl(G_layers,layers=True,

deg_corr=True,

state_args=dict(ec=G_layers.ep.layer,recs=[G_layers.ep.weight],rec_types=["real-exponential"],layers=True))

Then I got 10 communities. My questions:

1. Does it mean that in each year there are 10 communities , i.e., the

number of communities remains constant over time ?

2. If so, how can we detect the change in the number of communities as the

time goes by? As time goes by, some communities may disappear or merge with

other communities, or the whole network becomes more homophily and forms one

community.

It will be appreciated if you can help me.

Best regards,

Jianjian