In transportation, communication, social and other real networks, there are some critical edges play an important role in the delivery of traffic flow and information packets. Identifying critical edges in complex networks is of great significance in both theoretical studies and practical applications  . Considering the overlap of communities in the neighborhood of edges, a novel and effective index named subgraph overlap (SO) is proposed in this paper. Experimental results on one synthetic and eight real networks show that SO outperforms five benchmark methods in identifying critical edges which are crucial in maintaining the integrity of the structure and functions of networks.
In transportation, communication, social and other real complex networks, some critical edges act a pivotal part in controlling the flow of information and maintaining the integrity of the structure. Due to the importance of critical edges in theoretical studies and practical applications , the identification of critical edges gradually become a hot topic in current researches . Considering the overlap of communities in the neighborhood of edges, a novel and effective metric named subgraph overlap (SO) is proposed to quantifying the significance of edges. The experimental results show that SO outperforms all benchmarks in identifying critical edges which are crucial in maintaining the integrity of the structure and functions of networks.
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