<｜begin▁of▁sentence｜>### Instruction:
As a journal editor in the field of network science, you've been overseeing a series of papers in which the authors have created multiple synthetic networks following Erdős-Rényi model, with nodes in these networks having overlaps. To facilitate the reviewers to understand and evaluate these works better, highlight a query you'd like the authors to explicitly address in their revised submission: 

Could the authors elucidate how they've gone about identifying the largest ‘connected component’ which is common across these synthetic networks? Further, could they specify how they've determined the original indices of the nodes that make up this intersecting segment within all the individual networks? This additional analysis should significantly add value to the authors' present findings. Don't forget to include how this process has been integrated with the networkx API in their methodology.
### Response:
import networkx as nx
from graspologic.utils import multigraph_lcc_intersection

# Create three synthetic graphs with some common nodes
G1 = nx.erdos_renyi_graph(100, 0.05)
G2 = nx.erdos_renyi_graph(100, 0.05)
G3 = nx.erdos_renyi_graph(100, 0.05)

# Make sure there is overlap in the largest connected components
for i in range(10):
    G2.add_edge(i, i+1)
    G3.add_edge(i, i+1)

# Find the intersection of the largest connected components
graphs = [G1, G2, G3]
intersection_graph, inds = multigraph_lcc_intersection(graphs, return_inds=True)

# Check the number nodes in the intersection graph
print('Number of nodes in the intersection graph:', intersection_graph.number_of_nodes())

# Show indices of nodes in the intersection graph
print('Indices of nodes in the intersection graph:', inds)
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