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license: unknown |
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language: |
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- de |
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tags: |
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- historical |
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- newspapers |
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--- |
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# SentiAnno: A Sentiment-Annotated Corpus of Austrian Historical Newspapers |
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This repository hosts training, development and test splits for the recently introduced "SentiAnno" dataset from the ["Constructing a Sentiment-Annotated Corpus of Austrian Historical |
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Newspapers: Challenges, Tools, and Annotator Experience"](https://aclanthology.org/2024.nlp4dh-1.6/) paper by [Lucija Krušic](https://huggingface.co/lukru). |
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More from the paper: |
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> 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. |
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# Dataset Stats |
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We create a 80/10/10 dataset split from the gold standard annotations, using the [`0ecb222`](https://github.com/lucijakrusic/SentiAnno/tree/0ecb2228e6c290dd22836024f32e559cc9b9711e) revision. |
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Label negative has 447 sentences |
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Label mixed has 56 sentences |
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Label positive has 81 sentences |
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Label neutral has 345 sentences |
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For each label category (`positive`, `negative`, `neutral`, `mixed`) this dataset split ratio is performed leading to: |
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* 741 training examples |
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* 93 development examples |
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* 95 test examples |
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# License |
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License is still be to cleared out, for now it is "unknown". |
