<｜begin▁of▁sentence｜>### Instruction:
As a network analyst working for a social media platform, I need to use the SCD model from the WWW '14 paper 'High Quality, Scalable and Parallel Community Detection for Large Real Graphs' to detect the community structure in a network of 100 users. The probability of connection between any two users is 0.05. I want to identify the cluster memberships of each user to better understand their interactions and improve the recommendation system.
### Response:
import networkx as nx
from karateclub import SCD

# Step 1: Create a random graph using NetworkX
G = nx.erdos_renyi_graph(100, 0.05)

# Step 2: Initialize the SCD model
model = SCD(iterations=25, eps=10**-6, seed=42)

# Step 3: Fit the model on the graph
model.fit(G)

# Step 4: Get the cluster memberships
memberships = model.get_memberships()

print(memberships)
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