<｜begin▁of▁sentence｜>### Instruction:
As a Policy Researcher specializing in network analysis, you are tasked with analyzing the coauthorship relationships within the field of network science, as captured in a gml file named 'netscience.gml'. Your goal is to utilize the Louvain method available in the cdlib library to conduct community detection on the coauthorship network. Following this, you are required to compute the Newman-Girvan modularity as a fitness metric to assess the quality of the community partitioning obtained from the network. This analysis will provide valuable insights into the underlying structures and relationships within the network science community, enabling informed decision-making and strategic planning in the field.
### Response:
import networkx as nx
from cdlib import algorithms

# Load the coauthorships in network science graph
G = nx.read_gml('netscience.gml')

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

# Compute the fitness result of the given partitioning
fitness = communities.newman_girvan_modularity()

# Print result
print(fitness.score)
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