Dataset of networks used in assessing the Bayan algorithm for community detection

This dataset contains a wide range of randomly generated networks (random graphs) from a study on community detection. In total there are 1020 network files. This includes 500 ABCD graphs, 500 LFR graphs, 10 Erdos-Renyi graphs, and 10 Barabasi-Albert graphs as described in the article linked below this description. Each network is provided in .gml format.This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as they provide citations to this data repository (https://doi.org/10.6084/m9.figshare.22442785) and the reference article listed below (http://dx.doi.org/10.48550/arXiv.2209.04562), and license the new creations under the identical terms.For more information about the data, one may refer to the articles below:Aref, Samin, Hriday Chheda, and Mahdi Mostajabdaveh. "The Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity." arXiv preprint arXiv:2209.04562 (2022).Aref, S., Mostajabdaveh, M., Chheda, H. (2023). Heuristic Modularity Maximization Algorithms for Community Detection Rarely Return an Optimal Partition or Anything Similar. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10476. Springer, Cham. https://doi.org/10.1007/978-3-031-36027-5_48