<｜begin▁of▁sentence｜>### Instruction:
As a Quality Assurance Tester, you're tasked with ensuring that software meets quality standards and functional requirements. Imagine you're testing a new social networking application that visualizes community structures within user networks. To validate its functionality, you need to conduct a test using a simulated network graph.

Your task is to generate a tree graph representing a simplified user network with 7 users (labeled from 0 to 6). Each user is connected according to the tree structure, where non-leaf users have exactly 2 children. After simulating the network, you'll apply the edge betweenness centrality approach, a method for detecting community structures, to identify clusters within the user network.

To visualize the clustering results, you'll utilize the `plot` method from the Cut class in the igraph library. This will allow you to visually assess how effectively the application identifies and displays community structures within the user network.
### Response:
from igraph import Graph
import matplotlib.pyplot as plt

# Create a simple graph
g = Graph.Tree(7, 2)

# Perform a community detection to get a VertexClustering object
communities = g.community_edge_betweenness()
clustering = communities.as_clustering()

# Visualize the clustering
fig, ax = plt.subplots()
clustering.plot(context=ax)
plt.show()
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