<｜begin▁of▁sentence｜>### Instruction:
Given two community structures represented by membership lists or Clustering objects, can you calculate the split-join distance to understand the similarity between these two partitions of a set? The split-join distance can provide insight into whether one partition is a subpartition of the other or if they are very dissimilar.
### Response:
from igraph import Graph, Clustering

# Assuming we have two community structures defined
comm1 = Clustering([0, 0, 1, 1, 0, 1])
comm2 = Clustering([0, 0, 0, 1, 1, 1])

# Calculate the split-join distance
split_join_dist = Graph.split_join_distance(comm1, comm2)

# Print the split-join distance
print('Split-join distance:', sum(split_join_dist))
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