<｜begin▁of▁sentence｜>### Instruction:
As a naturalist leading a nature walk in a local park, imagine you want to demonstrate the concept of interconnectedness in a small ecosystem. You have a group of 100 nature enthusiasts in the park and you want to show them how each organism is connected to its three nearest neighbors in the ecosystem and how new connections can be formed with a probability of 0.5. You want to apply the BigClam model to illustrate how organisms can be grouped based on their interconnectedness and interactions within the ecosystem.
### Response:
import networkx as nx
from karateclub import BigClam

# Create a synthetic graph
G = nx.newman_watts_strogatz_graph(100, 3, 0.5)

# Initialize the BigClam model
model = BigClam(dimensions=10, iterations=100, learning_rate=0.01, seed=90)

# Fit the model
model.fit(G)

# Get the embedding and memberships
embedding = model.get_embedding()
memberships = model.get_memberships()

print('Embedding:', embedding)
print('Memberships:', memberships)
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