Datasets › Angry Tweets

Angry Tweets

Introduced by Amalie Brogaard Pauli et al. in DaNLP: An open-source toolkit for Danish Natural Language Processing1 May 2021 archive 2025-07-28

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:

  • Tasks: The dataset is suitable for text classification, specifically sentiment classification.
  • Languages: The dataset is in Danish.
  • Size Categories: The dataset falls in the size category of 1K<n<10K.
  • Annotations Creators: The annotations were created through crowdsourcing.

Each 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.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

CC BY 4.0 license

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • Angry Tweets

1 variant name, as the archive lists them.

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