<｜begin▁of▁sentence｜>### Instruction:
Imagine we're crafting a new group activity at our rehabilitation center, designed to engage participants in building their social network through a fun and interactive game. The objective of the game is to illustrate the growth of social connections over time, and for this, we'll create a simulated network that mirrors real-life social patterns. 

We'll use a virtual "Social Expansion" model, reflective of the Barabási–Albert model, with 10 players representing the nodes in the network. As the game progresses, each new participant (node) will introduce themselves and establish connections (edges) with 2 existing participants, simulating the natural tendency of people to form ties with others. In order to keep our game consistent and repeatable for future groups, we'll set the randomness of our connections using a special game sequence number, let's call it the 'luck factor', with a value of 42.

I'm asking you to initialize our "Social Expansion" simulation with these specifics and then compile a roster of the friendships (edges) formed. This roster will help us analyze and explain the growth of the network to our participants, providing them with insights into how their social circles can expand. Could you assist us with this?
### Response:
import networkx as nx

# Parameters
num_nodes = 10
num_edges_per_node = 2
seed = 42

# Generate a Barabási–Albert graph
BA_graph = nx.barabasi_albert_graph(num_nodes, num_edges_per_node, seed=seed)

# Print the edge set of the graph
echo = BA_graph.edges()
print(echo)
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