  Complex networks are made up of vertices and edges. The latter connect the
vertices. There are several ways to measure the importance of the vertices,
e.g., by counting the number of edges that start or end at each vertex, or by
using the subgraph centrality of the vertices. It is more difficult to assess
the importance of the edges. One approach is to consider the line graph
associated with the given network and determine the importance of the vertices
of the line graph, but this is fairly complicated except for small networks.
This paper compares two approaches to estimate the importance of edges of
medium-sized to large networks. One approach computes partial derivatives of
the total communicability of the weights of the edges, where a partial
derivative of large magnitude indicates that the corresponding edge may be
important. Our second approach computes the Perron sensitivity of the edges. A
high sensitivity signals that the edge may be important. The performance of
these methods and some computational aspects are discussed. Applications of
interest include to determine whether a network can be replaced by a network
with fewer edges with about the same communicability.
