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Although most of the real networks contain a mixture of directed and bidirectional (reciprocal) connections, the reciprocity has received little attention as a subject of theoretical understanding. We study the expected reciprocity of networks with an arbitrary degree sequence and a broad class of degree correlations by means of statistical ensemble approach. We demonstrate that degree correlations are crucial to understand the reciprocity in real networks and a hierarchy of correlation contributions to is revealed. Numerical experiments using novel network randomization methods show very good agreement to our analytical estimations.

生成讲解博客的中文版本

生成AI智能校验的中文版本