<｜begin▁of▁sentence｜>### Instruction:
As a systems analyst, you may encounter a scenario where a company wants to analyze the network structure of its 100 users and identify clusters within the network. This can be achieved using the SymmNMF algorithm to obtain node embeddings and cluster memberships. Suppose the company has collected data on the connections between users in the network, as well as additional attributes of the users. In this case, you can integrate the SymmNMF model, which is available in the networkx library, to analyze the network structure and identify clusters of users based on their connections and attributes.
### Response:
import networkx as nx
from karateclub import SymmNMF

# Create a random graph using networkx
G = nx.erdos_renyi_graph(n=100, p=0.05)

# Initialize the SymmNMF model with default parameters
model = SymmNMF()

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

# Retrieve the embeddings
embeddings = model.get_embedding()

# Retrieve the memberships
memberships = model.get_memberships()

# To use, print or analyze the embeddings and memberships
print(embeddings)
print(memberships)
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