<｜begin▁of▁sentence｜>### Instruction:
As a data analyst for a social media marketing company, I need to analyze the relationships between adjectives and nouns commonly used in our clients' posts. I have uploaded the Adjective-Noun Adjacency Graph, which I obtained from our social media data, to a GML file named adjnoun.gml.

Using the Louvain method in the cdlib library, I want to conduct community detection to identify groups of related adjectives and nouns within the graph. After obtaining the partitioning, I need to compute the modularity density to evaluate the quality of the identified communities.

I aim to use this analysis to gain insights into the thematic patterns present in our clients' content, which in turn will help us tailor our marketing strategies for better engagement and reach.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Read the graph from a GML file
G = nx.read_gml('adjnoun.gml')

# Apply a community detection algorithm
communities = algorithms.louvain(G)

# Evaluate the modularity density
modularity_dense = evaluation.modularity_density(G, communities)

# Print the modularity density
print(modularity_dense.score)
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