Before revision:  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.
After revision:  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 to quantifying the significance of edges. The experimental results 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.