<｜begin▁of▁sentence｜>### Instruction:
As a network analysis consultant, imagine receiving a call from a research team at a social networking company. They are interested in using machine learning models to understand the multi-scale relationships between users in their network. They are specifically asking how they can use the Walklets model to generate node embeddings from a Newman-Watts-Strogatz small-world graph with 100 nodes, each connected to 3 neighbors, and with a 0.5 probability of adding a new edge. They seek approaches that can capture the complex interactions and connections between users at different levels within the network.
### Response:
import networkx as nx
from karateclub import Walklets
import numpy as np

# Generating a simple graph
G = nx.newman_watts_strogatz_graph(100, 3, 0.5)

# Initializing Walklets
model = Walklets(
    walk_number=10,
    walk_length=80,
    dimensions=32,
    workers=4,
    window_size=4,
    epochs=1,
    learning_rate=0.05,
    min_count=1,
    seed=42
)

# Fitting the model
model.fit(G)

# Getting the embeddings
embeddings = model.get_embedding()

print(embeddings)
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