<｜begin▁of▁sentence｜>### Instruction:
Imagine we're crafting a strategic roadmap for a campaign, visualizing the flow of communication from our brand to various target segments. Our current strategy map is sketched out in the form of a directed influence diagram with nodes representing communication actions and edges indicating the direction of the strategic influence. The edges in our strategy diagram are as follows: from action 1 to action 2, from action 1 to action 3, from action 2 to action 3, from action 3 to action 4, and from action 3 to action 5.

As we reassess our campaign’s impact, we’re interested in exploring the strategy from the perspective of the consumer feedback loop, effectively turning the flow of influence on its head to help us understand how consumer reactions might drive our future actions. We’d like to employ NetworkX to transform our current strategy diagram into a reverse diagram, effectively swapping the source and target of each influence action.

Would you be able to advise on how we can invert our strategic influence diagram utilizing NetworkX, ensuring that each vector of influence is flipped to reflect this new consumer-centric perspective?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph([(1, 2), (1, 3), (2, 3), (3, 4), (3, 5)])

# Returns a new graph which is the reverse of G
G_reversed = nx.reverse(G)

# Print the edges of the reversed graph
print(G_reversed.edges())
# Output: OutEdgeView([(2, 1), (3, 1), (3, 2), (4, 3), (5, 3)])
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