<｜begin▁of▁sentence｜>### Instruction:
As a Brewmaster overseeing the brewing process, you have a network of coauthorships among researchers who specialize in different aspects of beer production. Using the Louvain's function in the cdlib library, you wish to detect communities within this network to better understand the collaborations and interactions between researchers. Additionally, you are interested in computing the Normalized Cut to gain insights into the division of these communities in relation to the entire network. This analysis will help you identify key groups and their interactions, aiding in the continuous enhancement and production of quality beer.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Create a graph
G = nx.read_gml('netscience.gml')

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

# Compute the normalized cut for the partitioning
normalized_cut_score = evaluation.normalized_cut(G, communities)

# Print the normalized cut score
print(normalized_cut_score)
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