{"url":"/dataset/twbnt","name":"TwBNT","full_name":null,"description_markdown":"TwBNT is the bot detection benchmark with automatic troll annotations.","description_withheld":null,"homepage":"","introduced_date":"2023-12-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/sega-preference-aware-self-contrastive","title":"SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter","first_author":"Ying-Ying Chang","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["TwBNT"],"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":"2026-09-25T09:33:49+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."}