<｜begin▁of▁sentence｜>### Instruction:
Given a list of NetworkX multigraph objects that represent different social networks with overlapping users, how can one find the union of these networks and extract the largest connected component to study the core interconnectivity between users?
### Response:
import networkx as nx
from graspologic.utils import multigraph_lcc_union

# Generate synthetic multigraphs
G1 = nx.MultiGraph()
G2 = nx.MultiGraph()
G1.add_edges_from([(1, 2), (2, 3)])
G2.add_edges_from([(3, 4), (4, 5), (4, 5)])

# List of multigraphs
graphs = [G1, G2]

# Find the union of multigraphs and compute the largest connected component
largest_component_graph = multigraph_lcc_union(graphs)

# Print nodes of the largest connected component
print(largest_component_graph.nodes())

# If return_inds is True, also get the indices of the nodes in the original graphs
largest_component_graph, kept_indices = multigraph_lcc_union(graphs, return_inds=True)
print('Indices kept:', kept_indices)
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