<｜begin▁of▁sentence｜>### Instruction:
As a paralegal tasked with constructing a case around the interactions within a corporate network, you've been presented with data detailing the connections between various entities. The network data, encapsulating relations akin to edges in a graph, includes the tuple set: [(1, 2), (1, 3), (2, 4)]. Your assignment is to methodically review the network, utilizing the AdjacencyView provided by NetworkX, to map out which entities directly associate with one another, thereby revealing the neighbors for each individual node within this corporate framework. Could you envision a scenario where this examination aids in clarifying the nature of the communications or transactions under legal scrutiny?
### Response:
import networkx as nx

# Create a new graph
G = nx.Graph()
# Add some edges
G.add_edges_from([(1, 2), (1, 3), (2, 4)])

# Get the Adjacency View of the graph
adjacency_view = G.adjacency()

# Iterate through the adjacency view and print
for node, neighbors in adjacency_view:
    print(f'Node {node} has neighbors {list(neighbors.keys())}')
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