{"url":"/dataset/mag-scholar-c-1","name":"MAG-Scholar-C","full_name":null,"description_markdown":"MAG-Scholar-C is constructed by Bojchevski et al. based on Microsoft Academic Graph (MAG), in which nodes refer to papers, edges represent citation relations among papers and features are bag-of-words  of paper abstracts.","description_withheld":null,"homepage":"https://figshare.com/articles/dataset/mag_scholar/12696653","introduced_date":"2020-07-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/scaling-graph-neural-networks-with","title":"Scaling Graph Neural Networks with Approximate PageRank","first_author":"Aleksandar Bojchevski","url":null},"license":null,"modalities":[],"tasks":[{"name":"Node Classification","url":"/task/node-classification","datasets_with_task":"/datasets/task/node-classification"}],"languages":[],"variants":["MAG-Scholar-C"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/node-classification-on-mag-scholar-c","task":"Node Classification","dataset_variant":"MAG-scholar-C","rows":4,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"FastGCN","paper":"/paper/grand-scalable-graph-random-neural-networks","metrics":{"Accuracy":"64.3"},"code_links":[{"title":"wzfhaha/grand-plus","url":"https://github.com/wzfhaha/grand-plus"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/grand-scalable-graph-random-neural-networks","title":"GRAND+: Scalable Graph Random Neural Networks","date":"2022-03-12","rows_on_this_dataset":4,"code_links":1,"syntology":null}],"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."}