<｜begin▁of▁sentence｜>### Instruction:
As a network analyst working with a research institution, you have been tasked with using the Louvain community detection algorithm in the Community Discovery Library (cdlib) to identify collaborative communities within the High-energy theory network. You are also required to compute the normalized cut, which is a variation of the Cut-Ratio, for the identified communities. The network data is available in a GML file named "hep-th.gml," which contains information about collaborations among researchers in the high-energy theory field. Your analysis will help in understanding the structure of the research collaborations and relationships within the network.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Load the High-energy theory collaborations graph
G = nx.read_gml('hep-th.gml')

# Perform community detection using the Louvain method
communities = algorithms.louvain(G)

# Compute the normalized cut of the identified communities
norm_cut = evaluation.normalized_cut(G, communities)

# Print the result
print(norm_cut)
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