<｜begin▁of▁sentence｜>### Instruction:
Alright, so picture this: you're walking into my store, and I've got this amazing puzzle on the shelf, called the "big network challenge." It's a hot seller Ã¢ÂÂ people love figuring out connections, patterns, and seeing how things spread, just like how a new product takes off in the market. Now, imagine the puzzle is a network, a big spaghetti bowl of nodes and edges, representing all our customers and how they influence each other.

Now, you, my friend, have come in looking for a more hands-on, personal experience with this puzzle. You're not interested in the whole thing; you want a piece of it, something more manageable, just like when you're targeting a specific audience for a high-end product. So here's what we'll do: we're gonna use this cool tool called the DiffusionSamplerÃ¢ÂÂthink of it as a spotlight that's going to shine on the most connected, influential 50 customers in this network, based on who talks to whom and how those conversations spread.

So, to keep it in our language, let's imagine I've got your network data in this nifty 'littleballoffur12.gml' file. How would we use that DiffusionSampler to create a VIP list of the top 50 nodes, just like when we're picking out the best leads from a client list? We want to see how those few can make the biggest splash, just like in spreading the word about our next big sale. How about it?
### Response:
import networkx as nx
from littleballoffur.exploration_sampling import DiffusionSampler
G = nx.read_sparse6('littleballoffur12.sparse6')
sampler = DiffusionSampler(number_of_nodes=50, seed=42)
sampler_G = sampler.sample(G)
print(sampler_G.edges(), sampler_G.nodes())
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