--- 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"](https://aclanthology.org/2024.nlp4dh-1.6/) paper by [Lucija KruĊĦic](https://huggingface.co/lukru). 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`](https://github.com/lucijakrusic/SentiAnno/tree/0ecb2228e6c290dd22836024f32e559cc9b9711e) 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".