{"url":"/dataset/angry-tweets","name":"Angry Tweets","full_name":null,"description_markdown":"The Angry Tweets dataset is a collection of anonymized Danish Twitter data that has been annotated for sentiment analysis through crowd-sourcing. Here are some key details about the dataset:\r\n\r\n- **Tasks**: The dataset is suitable for text classification, specifically sentiment classification.\r\n- **Languages**: The dataset is in Danish.\r\n- **Size Categories**: The dataset falls in the size category of 1K<n<10K.\r\n- **Annotations Creators**: The annotations were created through crowdsourcing.\r\n\r\nEach entry in the dataset has a tweet and an associated label. The label can be \"positiv\", \"neutral\", or \"negativ\" for positive, neutral, and negative sentiment, respectively. The dataset is split into a training set and a test set, with the test set being 30% of the dataset, randomly sampled in a stratified fashion.","description_withheld":null,"homepage":"https://huggingface.co/datasets/DDSC/angry-tweets","introduced_date":"2021-05-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/danlp-an-open-source-toolkit-for-danish","title":"DaNLP: An open-source toolkit for Danish Natural Language Processing","first_author":"Amalie Brogaard Pauli","url":null},"license":{"name":"CC BY 4.0 license","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["Angry Tweets"],"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."}