<｜begin▁of▁sentence｜>### Instruction:
As a laboratory technician, you have been tasked with analyzing the network of common adjectives and nouns in the novel "David Copperfield" by Charles Dickens. The network data is stored in a gml file named adjnoun.gml. Your goal is to apply the Louvain and Leiden community detection algorithms to identify communities of related words. Once the communities are identified, you need to compute the Normalized F1 score to evaluate the similarity between the resulting partitions. This analysis will help in understanding the semantic relationships between the words and their associations within the novel.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Load a graph of word adjacencies
G = nx.read_gml('adjnoun.gml')

# Apply two community detection algorithms to the graph
louvain_communities = algorithms.louvain(G)
leiden_communities = algorithms.leiden(G)

# Compute the Normalized F1 score between the partitions
nf1_score = evaluation.nf1(louvain_communities, leiden_communities)

# Print the Normalized F1 score
print(nf1_score.score)
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