{"url":"/dataset/goemotions","name":"GoEmotions","full_name":"GoEmotions","description_markdown":"**GoEmotions** is a corpus of 58k carefully curated comments extracted from Reddit, with human annotations to 27 emotion categories or Neutral.\r\n\r\n- Number of examples: 58,009.\r\n- Number of labels: 27 + Neutral.\r\n- Maximum sequence length in training and evaluation datasets: 30.\r\n\r\nOn top of the raw data, the dataset also includes a version filtered based on reter-agreement, which contains a train/test/validation split:\r\n\r\n- Size of training dataset: 43,410.\r\n- Size of test dataset: 5,427.\r\n- Size of validation dataset: 5,426.\r\n\r\nThe emotion categories are: admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise.\r\n\r\nSource: [Google Research](https://github.com/google-research/google-research/tree/master/goemotions)","description_withheld":null,"homepage":"https://github.com/google-research/google-research/tree/master/goemotions","introduced_date":"2020-05-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/goemotions-a-dataset-of-fine-grained-emotions","title":"GoEmotions: A Dataset of Fine-Grained Emotions","first_author":"Dorottya Demszky","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Multi Label Text Classification","url":"/task/multi-label-text-classification-1","datasets_with_task":"/datasets/task/multi-label-text-classification-1"}],"languages":[],"variants":["GoEmotions","go_emotions"],"data_loaders":[{"repo":"https://github.com/google-research/google-research","url":"https://github.com/google-research/google-research","frameworks":["tf"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/go_emotions","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/BDas/Turkish-Dataset","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/antoniomenezes/go_emotions_ptbr","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/google-research-datasets/go_emotions","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/tensorflow/datasets","url":"https://www.tensorflow.org/datasets/catalog/goemotions","frameworks":["tf","jax"]}],"num_papers_in_archive":130,"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."}