<｜begin▁of▁sentence｜>### Instruction:
Imagine that you're developing an educational module on social network analysis using NetworkX for a course on advanced network theory. As part of an interactive activity within this module, you want the learners to explore the concept of group betweenness centrality in the context of a well-known social network, such as the Zachary's Karate Club network. To demonstrate their understanding, the learners are tasked with identifying a specific subgroup within the network. Specifically, they need to determine which trio of individuals forms the most significant subgroup in terms of their group betweenness centrality.

In this exercise, the data is embedded within NetworkX's library of graph examples, specifically within the "karate_club_graph" dataset. The learners will use Python programming and NetworkX methods to analyze this dataset. Your instructional challenge is to craft a scenario where the learners must apply their skills to find out which group of three members from the Karate Club graph holds the greatest influence over the flow of information as measured by their collective betweenness centrality. How would you formulate this task in the educational materials for this course?
### Response:
import networkx as nx
from networkx.algorithms.centrality import prominent_group

# Create a graph
G = nx.karate_club_graph()

# Define number of nodes in the prominent group
k = 3

# Compute prominent group with k members
max_GBC, max_group = prominent_group(G, k)

print('The group betweenness centrality of the prominent group:', max_GBC)
print('The list of nodes in the prominent group:', max_group)
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