README.md

metadata

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

Dataset Card for DKHate

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

• Direct Download: http://danlp-downloads.alexandra.dk/datasets/europarl.sentiment2.zip

Dataset Summary

This dataset consists of Danish data from the European Parliament that has been annotated for sentiment analysis by the Alexandra Institute - all credits go to them.

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 document and an associated label.

Data Fields

An entry in the dataset consists of the following fields:

• text (str): The text 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 669 documents in the training split and 288 in the test split.

Additional Information

Dataset Curators

The collection and annotation of the dataset is solely due to the Alexandra Institute.

Licensing Information

The dataset is released under the CC BY 4.0 license.

Citation Information

@misc{europarl,
  title={EuroParl},
  author={Alexandra Institute},
  year={2020},
  note={\url{https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#europarl-sentiment2}}
}

Contributions

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