AbstractDescribing variation of species interaction networks across space and time promises a better understanding of how species communities respond to global change. To understand this variation, it has been suggested to partition network dissimilarity into one component driven by species turnover, that is, changes in community composition, and another component reflecting rewiring, that is, flexibility of interactions among shared species. The latter makes a strong case for investing the enormous effort in empirically recording interactions, instead of simply building networks based on community data. Here, I present a flexible R function (available in the R package bipartite) to calculate network dissimilarity and its components, with binary and quantitative networks. With this new tool, I compare two published methods for partitioning network dissimilarity, using conceptual examples, published plant–pollinator networks, and a set of simulations. This comparison highlights that the method that has received most attention overestimates the importance of rewiring for total network dissimilarity. In contrast, an earlier‐proposed method is derived from additive partitioning of the sets of interactions and thus accurately represents the two dissimilarity components. Furthermore, I argue that the term rewiring is not well defined in network ecology and that there are reasons why both methods overestimate the importance of rewiring, in particular with quantitative networks. The availability of a unified function to calculate multiple aspects of network dissimilarity will foster its critical application to characterize network dynamics and to identify underlying drivers. Studies on network dissimilarity and rewiring will have to be more careful in the choice of method and its interpretation.