<｜begin▁of▁sentence｜>### Instruction:
Certainly! Imagine you are a researcher studying the dynamics of social networks. You have collected data from a group of 200 individuals and their interactions, represented as an erdos_renyi_graph. Now, you want to use DiffusionTreeSampler to select a subset of 50 nodes from the network and visualize the spread of influence using a diffusion branching process. This will help you understand how information or behavior propagates within a smaller community, and how it relates to the larger network.
### Response:
import networkx as nx
from littleballoffur import DiffusionTreeSampler

G = nx.gnp_random_graph(n=200, p=0.4)

sampler = DiffusionTreeSampler(number_of_nodes=50, seed=100)

sampler_G = sampler.sample(G)

print(sampler_G.nodes())
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