{"url":"/dataset/collate","name":"CollATe","full_name":null,"description_markdown":"The **CollATe** dataset is large dataset consisting of two types of collusive entities on YouTube – videos submitted to gain collusive likes and comment requests, and channels submitted to gain collusive subscriptions.","description_withheld":null,"homepage":"https://github.com/LCS2-IIITD/CollATe/tree/master/data","introduced_date":"2020-05-13","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Detecting and analyzing collusive entities on YouTube","first_author":null,"url":null},"license":{"name":"Unknown","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["CollATe"],"data_loaders":[{"repo":"https://github.com/LCS2-IIITD/CollATe","url":"https://github.com/LCS2-IIITD/CollATe","frameworks":[]}],"num_papers_in_archive":3,"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."}