license: unknown
language:
- de
tags:
- historical
- newspapers
SentiAnno: A Sentiment-Annotated Corpus of Austrian Historical Newspapers
This repository hosts training, development and test splits for the recently introduced "SentiAnno" dataset from the "Constructing a Sentiment-Annotated Corpus of Austrian Historical Newspapers: Challenges, Tools, and Annotator Experience" paper by Lucija Krušic.
More from the paper:
This study presents the development of a sentiment-annotated corpus of historical newspaper texts in Austrian German, addressing a gap in annotated corpora for Natural Language Processing in the field of Digital Humanities. Three annotators categorised 1005 sentences from two 19th-century periodicals into four sentiment categories: positive, negative, neutral, and mixed. The annotators, Masters and PhD students in Linguistics and Digital Humanities, are considered semi-experts and have received substantial training during this annotation study.
Dataset Stats
We create a 80/10/10 dataset split from the gold standard annotations, using the 0ecb222 revision.
For each label category (positive, negative, neutral, mixed) this dataset split ratio is performed leading to:
- 741 training examples
- 93 development examples
- 95 test examples
Dataset splits were created using this notebook.
Dataset Usage
An example notebook shows how to use this dataset with the awesome Flair library.
Acknowledgements
Many thanks to Lucija Krušic for releasing the SentiAnno dataset!
License
License is still be to cleared out, for now it is "unknown".