  Algorithms to find communities in networks rely just on structural
information and search for cohesive subsets of nodes. On the other hand, most
scholars implicitly or explicitly assume that structural communities represent
groups of nodes with similar (non-topological) properties or functions. This
hypothesis could not be verified, so far, because of the lack of network
datasets with information on the classification of the nodes. We show that
traditional community detection methods fail to find the metadata groups in
many large networks. Our results show that there is a marked separation between
structural communities and metadata groups, in line with recent findings. That
means that either our current modeling of community structure has to be
substantially modified, or that metadata groups may not be recoverable from
topology alone.
