<｜begin▁of▁sentence｜>### Instruction:
Suppose you are a Digital Marketing Specialist working on a project where you need to analyze online user behaviors. You decided to employ a bipartite graph to categorize users and their behaviors, where one set of nodes represents the users and the other represents their behaviors. The first set needs to have 10 nodes, representing 10 different users, while the second set should contain 20 nodes, symbolizing 20 unique behaviors. Additionally, you need 50 edges in total to represent the relationships. 

How would you construct such a bipartite graph using NetworkX's 'gnmk_random_graph' function without generating a directed graph, guaranteeing repeatability via a seed value? Remember, this is crucial in ensuring the consistency of your marketing strategy testing and modifications.
### Response:
import networkx as nx
from networkx.algorithms import bipartite

# Generate a random bipartite graph G_{n,m,k}
G = bipartite.gnmk_random_graph(10, 20, 50, seed=42, directed=False)

# Print basic information about the graph
print('Graph has', G.number_of_nodes(), 'nodes and', G.number_of_edges(), 'edges.')
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