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.
Label negative has 447 sentences Label mixed has 56 sentences Label positive has 81 sentences Label neutral has 345 sentences
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
License
License is still be to cleared out, for now it is "unknown".