<｜begin▁of▁sentence｜>### Instruction:
As a talent agent representing a diverse group of musicians, you have 10 artists under your management and have facilitated collaborative projects resulting in 20 new musical compositions. You need to utilize a tool like the bibcoupling method in the NetworkX API to calculate the level of thematic overlap, or "bibliographic coupling scores," between each pair of artists based on their collaborative works. Can you provide me with the bibliographic coupling matrix to identify the strength of connections between these talented individuals?
### Response:
import igraph as ig

# Create an example graph
g = ig.Graph.Erdos_Renyi(n=10, m=20)

# Calculate bibliographic coupling scores for all vertices
scores_matrix = g.bibcoupling()

# Print the bibliographic coupling matrix
for row in scores_matrix:
    print(row)
<|EOT|>
