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Dynamical processes, such as the diffusion of knowledge, opinions, pathogens,"fake news", innovation, and others, are highly dependent on the structure ofthe social network on which they occur. However, questions on why most socialnetworks present some particular structural features, namely high levels oftransitivity and degree assortativity, when compared to other types of networksremain open. First, we argue that every one-mode network can be regarded as aprojection of a bipartite network, and show that this is the case using twosimple examples solved with the generating functions formalism. Second, usingsynthetic and empirical data, we reveal how the combination of the degreedistribution of both sets of nodes of the bipartite network --- together withthe presence of cycles of length four and six --- explains the observed levelsof transitivity and degree assortativity in the one-mode projected network.Bipartite networks with top node degrees that display a more right-skeweddistribution than the bottom nodes result in highly transitive and degreeassortative projections, especially if a large number of small cycles arepresent in the bipartite structure.

Transitivity and degree assortativity explained: The bipartite structure of social networks