<｜begin▁of▁sentence｜>### Instruction:
Given the American College football network data from a GML file named 'football.gml', how can we use the EVA algorithm from cdlib to perform community detection that incorporates node attributes, and then output the community structure in JSON format?
### Response:
import networkx as nx
from cdlib import algorithms
import random

# Load the graph
G = nx.read_gml('football.gml')

# Define the attributes for each node (assumed to be football positions)
labels = {node: {'position': random.choice(['QB', 'RB', 'WR', 'TE', 'LB', 'CB', 'S', 'OL', 'DL'])} for node in G.nodes()}

# Perform community detection using the EVA algorithm
communities = algorithms.eva(G, labels, alpha=0.5)

# Get the JSON representation of the community structure
community_json = communities.to_json()
print(community_json)
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