{"url":"/dataset/wnut-2020-task-2","name":"WNUT-2020 Task 2","full_name":"WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets","description_markdown":"Briefly describe the dataset. Provide:\r\n\r\n* a high-level explanation of the dataset characteristics\r\n* explain motivations and summary of its content\r\n* potential use cases of the dataset\r\n\r\nIf the description or image is from a different paper, please refer to it as follows:\r\nSource: [title](url)\r\nImage Source: [title](url)","description_withheld":null,"homepage":"","introduced_date":"2020-10-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/wnut-2020-task-2-identification-of","title":"WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets","first_author":"Dat Quoc Nguyen","url":null},"license":null,"modalities":[],"tasks":[{"name":"Text Classification","url":"/task/text-classification","datasets_with_task":"/datasets/task/text-classification"}],"languages":[],"variants":["WNUT-2020 Task 2"],"data_loaders":[],"num_papers_in_archive":28,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/text-classification-on-wnut-2020-task-2","task":"Text Classification","dataset_variant":"WNUT-2020 Task 2","rows":1,"metrics":["F1"],"first_row_in_archive_order":{"model":"NutCracker","paper":"/paper/nutcracker-at-wnut-2020-task-2-robustly","metrics":{"F1":"0.9096"},"code_links":[{"title":"kpriyanshu256/WNUT-2020-Task-2","url":"https://github.com/kpriyanshu256/WNUT-2020-Task-2"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/nutcracker-at-wnut-2020-task-2-robustly","title":"NutCracker at WNUT-2020 Task 2: Robustly Identifying Informative COVID-19 Tweets using Ensembling and Adversarial Training","date":"2020-10-09","rows_on_this_dataset":1,"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."}