README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - da
license:
  - cc-by-4.0
multilinguality:
  - monolingual
pretty_name: AngryTweets
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification

Dataset Card for AngryTweets

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Paper: https://aclanthology.org/2021.nodalida-main.53/
• Direct Download: https://danlp-downloads.alexandra.dk/datasets/game_tweets.zip

Dataset Summary

This dataset consists of anonymised Danish Twitter data that has been annotated for sentiment analysis through crowd-sourcing. All credits go to the authors of the following paper, who created the dataset:

Pauli, Amalie Brogaard, et al. "DaNLP: An open-source toolkit for Danish Natural Language Processing." Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). 2021

Supported Tasks and Leaderboards

This dataset is suitable for sentiment analysis.

Languages

This dataset is in Danish.

Dataset Structure

Data Instances

Every entry in the dataset has a tweet and an associated label.

Data Fields

An entry in the dataset consists of the following fields:

• text (str): The tweet content.
• label (str): The label of the text. Can be "positiv", "neutral" or "negativ" for positive, neutral and negative sentiment, respectively.

Data Splits

A train and test split is available, with the test split being 30% of the dataset, randomly sampled in a stratified fashion. There are 2,437 tweets in the training split and 1,047 in the test split.

Additional Information

Dataset Curators

The collection and annotation of the dataset is solely due to the authors of the original paper: Amalie Brogaard Pauli, Maria Barrett, Ophélie Lacroix and Rasmus Hvingelby. The tweets have been anonymised by @saattrupdan.

Licensing Information

The dataset is released under the CC BY 4.0 license.

Citation Information

@inproceedings{pauli2021danlp,
  title={DaNLP: An open-source toolkit for Danish Natural Language Processing},
  author={Pauli, Amalie Brogaard and Barrett, Maria and Lacroix, Oph{\'e}lie and Hvingelby, Rasmus},
  booktitle={Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)},
  pages={460--466},
  year={2021}
}

Contributions

Thanks to @saattrupdan for adding this dataset to the Hugging Face Hub.