<｜begin▁of▁sentence｜>### Instruction:
Imagine you're overseeing a network of rising stars—actors, musicians, and performers, labeled as 1, 2, 3, and 4. Their collaborations are akin to relationships, with duos such as 1 and 2, 1 and 3, and so on, forming partnerships like (1, 2), (1, 3), (3, 4), (1, 4), (2, 4). As a talent agent with an eye on the big picture, you're interested in knowing who among these talents serves as the most crucial bridge for connections and networking within this intricate web. In industry terms, which client holds the greatest "betweenness centrality" in this exclusive group? This is essential for maximizing opportunities and strategic planning in navigating the entertainment landscape.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (3, 4), (1, 4), (2, 4)])

# Compute the betweenness centrality of the graph
betweenness = nx.betweenness_centrality(G)

# Print the betweenness centrality of each node
for node, centrality in betweenness.items():
    print(f'Node {node}: {centrality}')
<|EOT|>
