<｜begin▁of▁sentence｜>### Instruction:
Given a random graph generated with the G(n,p) model using 100 nodes and a probability of 0.1 for edge creation, how can the SCD (Scalable Community Detection) algorithm from the WWW '14 paper be used to detect communities and what are the resulting memberships?
### Response:
import networkx as nx
from karateclub import SCD

# Create a random graph using NetworkX
G = nx.gnp_random_graph(100, 0.1, seed=42)

# Initialize SCD with default parameters
model = SCD()

# Fit SCD model on the graph
model.fit(G)

# Get the memberships of the nodes
memberships = model.get_memberships()

# Print the cluster membership for each node
print(memberships)
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