<｜begin▁of▁sentence｜>### Instruction:
Imagine you're part of a community where each individual (represented by nodes 0 to 3) has relationships with others (depicted as the connections between them). In this community, we've observed interactions that have resulted in a set of connections: individuals 0 and 1 have a bond, as do 0 and 2, 0 and 3, 1 and 2, and finally, 1 and 3. In order to provide personalized support and guidance, it would be beneficial to understand the prominence of each individual within the social structure based on the number of connections they have. Could you help us explore the concept of involvement of these members in the community by determining the degree centrality for each person using the tools provided by NetworkX? This will enable us to better understand who might benefit most from community resources due to their pivotal roles in the network.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])

# Calculate degree centrality
centrality = nx.degree_centrality(G)

# Print the degree centrality of each node
for node, cent in centrality.items():
    print(f'Node {node}: {cent}')
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