<｜begin▁of▁sentence｜>### Instruction:
As a market analyst tasked with analyzing the competitive landscape in the American College football industry, you are provided with a network graph file called "football.gml" containing connections between colleges. To enhance strategic planning and decision-making, your goal is to leverage the Louvain community detection algorithm available through the NetworkX library API to identify distinct communities within this network. Furthermore, you are required to compute and present the modularity score, a key metric indicating the strength of community structures within the graph.
### Response:
import networkx as nx
from cdlib import algorithms

# Read the American College football network graph
G = nx.read_gml('football.gml')

# Run the Louvain community detection algorithm
communities = algorithms.louvain(G, weight='weight', resolution=1.0)

# Evaluate modularity of the detected communities
modularity = communities.newman_girvan_modularity()
print('Modularity of the detected communities:', modularity)
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