Community-aware detection of anomalies 
This is the code for detecting node anomalies in networks with NetworkX by including community structure from two out-of-the-box community detection algorithm: (1) Louvain , and (2) Infomap . The algorithm is described here.
For (1), Python package Python-Louvain is used.
For (2), Python package Infomap is used.
 Helling, T.J., Scholtes, J. C., Takes, F.W. A community-aware approach for identifying node anomalies in complex networks. In Proceedings of the 7th International Conference on Complex Networks, CI, pages 244–255. Springer, 2019.
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 Rosvall, M., Bergstrom, C.: Maps of random walks on complex networks reveal community structure. Proceedings of National Academy of Sciences,105(4), 1118–1123 (2008)