<｜begin▁of▁sentence｜>### Instruction:
As a network analysis expert, I can help you with your query. Consider a scenario where you are analyzing a social network of 100 individuals, where each individual has a probability of 0.1 to be connected with others in the network. You are interested in implementing the SocioDim model to derive node embeddings for the individuals in the network. This model can provide insights into the structural and relational aspects of the social network, which can be valuable for understanding social dynamics and interactions.
### Response:
import networkx as nx
from karateclub import SocioDim

# Generate a random graph using NetworkX
G = nx.fast_gnp_random_graph(100, 0.1)

# Initialize SocioDim model with specified dimensions and seed
model = SocioDim(dimensions=128, seed=42)

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

# Get the embedding of nodes
embedding = model.get_embedding()

# Display the embedding
print(embedding)
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