Datasets:
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 DKHate
Table of Contents
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:
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 thetext
. 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.