<｜begin▁of▁sentence｜>### Instruction:
Imagine we are working on creating an accessible representation of a network shaped like a dodecahedron for a visually impaired student. This network should be illustrated using a tool like NetworkX linked with Matplotlib to ensure we can customize it appropriately. We need to adjust the presentation of each node, specifically altering attributes such as the labels associated with them. These labels need to be tailored in terms of font size, color, and family to enhance readability and aid in the student's understanding. Could you demonstrate how we might approach labeling each node within this dodecahedral graph network, considering these specific visual adjustments, without actually incorporating the execution steps in the explanation?
### Response:
import matplotlib.pyplot as plt
import networkx as nx

# Create a graph
G = nx.dodecahedral_graph()

# Define positions for each node
pos = nx.spring_layout(G)

# Draw the graph with node labels
def draw_graph_with_labels(G, pos):
    nx.draw(G, pos, with_labels=False)
    labels = nx.draw_networkx_labels(G, pos, font_size=12, font_color='black', font_family='sans-serif')
    plt.show()

draw_graph_with_labels(G, pos)
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