<｜begin▁of▁sentence｜>### Instruction:
Imagine we're conducting a study to understand social dynamics within a very small network of individuals, represented by a graph we have in our dataset. This graph resembles a barbell structure where we have two tight-knit groups of three friends each, metaphorically connected by a thin, single friendship linking the two trios. 

Our objective is to simulate a scenario where these two friend groups become entirely distinct by severing this single connecting friendship. We're interested in precisely quantifying the "social cut" necessary for this separation. Using the dataset we've collected (for example, in a GML file if that's the case), how could we employ the NetworkX library to calculate the minimum number of friendships that need to be removed for our groups to form two separate social circles, thus identifying the magnitude of this theoretical social divide?
### Response:
import networkx as nx

# Create a graph
G = nx.barbell_graph(3, 0)

# Define two sets of nodes
S = {0, 1, 2}
T = {3, 4, 5}

# Calculate the cut size between the two sets
cut_size_value = nx.cut_size(G, S, T)

print('Cut size between sets S and T:', cut_size_value)
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