{"url":"/dataset/dota-2-toxic-chat-data","name":"DOTA 2 toxic chat data","full_name":null,"description_markdown":"The dataset was collected from DOTA 2 using OpenDota API via Python. The collection consists of DOTA 2 in-game chat data that were manually categorized into 3 classifications: non-toxic, mild (toxicity), and toxic chats.\r\n\r\nTarget value categorization:\r\n0 = non-toxic \r\n1 = mild (toxicity)  \r\n2 = toxic","description_withheld":null,"homepage":"https://huggingface.co/datasets/dffesalbon/dota-2-toxic-chat-data","introduced_date":"2024-03-19","introduced_date_note":null,"introduced_by":{"paper":"/paper/fine-tuning-pre-trained-language-models-to","title":"Fine-Tuning Pre-trained Language Models to Detect In-Game Trash Talks","first_author":"Daniel Fesalbon","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["DOTA 2 toxic chat data"],"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."}