{"url":"/dataset/real-world-graphs-for-betweenness-centrality","name":"Real-world graphs for betweenness-centrality ranking estimation","full_name":null,"description_markdown":"The ground truth betweenness-centralities for the real-world graphs are provided by AlGhamdi et al. (2017), which are computed by the parallel implementation of Brandes algorithm on a 96000-core supercomputer. The ground truth scores for the synthetic networks are provided by Fan et al. (2019) and are computed using the graph-tool (Peixoto, 2014) library.\r\n\r\nThe presented approach is compared to several baseline models. The performance of those models are adopted from the benchmark provided by Fan et al. (2019):\r\n\r\nABRA (Riondato & Upfal, 2018): Samples pairs of nodes until the desired accuracy is reached. Where the error tolerance λ was set to 0.01 and the probability δ was set to 0.1.\r\n\r\nRK (Riondato & Kornaropoulos, 2014): The number of pairs of nodes is determined by the diameter of the network. Where the error tolerance and the probability were set similar to ABRA.\r\n\r\nk-BC (Pfeffer & Carley, 2012): Does only k steps of Brandes algorithm (Brandes, 2001) which was set to 20% of the diameter of the network.\r\n\r\nKADABRA (Borassi & Natale, 2019): Uses bidirectional BFS to sample the shortest paths. The variant where it computest the top-k% nodes with the highest betweenness-centrality was used. The error tolerance and probability were set to be the same as ABRA and RK.\r\n\r\nNode2Vec (Grover & Leskovec, 2016): Uses a biased random walk to aggregate information from the neighbors. The vector representations of each node were then mapped with a trained MLP to ranking scores.\r\n\r\nDrBC (Fan et al., 2019): Shallow graph convolutional network that outputs a ranking score for each node by propagating through the neighbors with a walk length of 5.","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Real-world graphs for betweenness-centrality ranking estimation"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}