DynComm: Dynamic Network Communities Detection
Bundle of algorithms used for evolving network analysis regarding community detection.
Implements several algorithms, using a common API, that calculate communities for graphs whose vertices and edges change over time. Edges, which can have new vertices, can be added or deleted, and changes in the communities are calculated without recalculating communities for the entire graph.
This package uses the following work as reference material for the implementation of the algorithms.
poltergeist0
GitHub project source Cordeiro M, Sarmento RP, Gama J (2016). “Dynamic community detection in evolving networks using locality modularity optimization.” Social Network Analysis and Mining, 6(1), 1–20. Rossetti G, Pappalardo L, Pedreschi D, Giannotti F (2017). “Tiles: An Online Algorithm for Community Discovery in Dynamic Social Networks.” Mach. Learn., 106(8), 1213–1241. ISSN 0885-6125, doi: 10.1007/s10994-016-5582-8, https://doi.org/10.1007/s10994-016-5582-8. Rossetti G (2017). “RDYN: Graph Benchmark handling Community Dynamics.” Journal of Complex Networks. doi: 10.1093/comnet/cnx016, https://academic.oup.com/comnet/article/5/6/893/3925036?guestAccessKey=c3470adf-391d-4fad-b935-63e71e4df06a. Sarmento RP (2019). “Density-based Community Detection/Optimization.” arXiv. 1904.12593, https://arxiv.org/abs/1904.12593.
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