<｜begin▁of▁sentence｜>### Instruction:
In my role as a mediator, I find myself in situations where it's essential to navigate complex networks of relationships and disputes. Imagine we are examining the intricate web of interactions within a community represented by a network graph. We have observed two notable patterns of interaction: the first involves participants 0, 1, 2, and 3, while the second connects participants 0, 3, 4, and 5.

To facilitate a more thorough understanding of this network's underlying structure, could you describe how a toolkit like NetworkX might assist us in identifying a foundational set of interaction cycles? Specifically, I'm interested in utilizing the cycle_basis function with participant 0 as a starting point to determine these foundational cycles. This understanding might be crucial in helping us uncover the minimal pathways that explain the entirety of this community's interactions, thereby enabling us to explore effective conflict resolution strategies tailored to their specific dynamic.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add cycles to the graph
nx.add_cycle(G, [0, 1, 2, 3])
nx.add_cycle(G, [0, 3, 4, 5])

# Find the cycle basis with a specified root node
root_node = 0
cycles = nx.cycle_basis(G, root_node)

print('Cycle basis:', cycles)
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