{
 "id": "clarin-pl/polemo2-official",
 "owner": "clarin-pl",
 "name": "polemo2-official",
 "downloads": 8535,
 "likes": 7,
 "last_modified": "2022-08-29T16:40:01.000Z",
 "stated_licence": "cc-by-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-classification"
 ],
 "citation": "@inproceedings{kocon-etal-2019-multi,\n    title = \"Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews\",\n    author = \"Koco{\\'n}, Jan  and\n      Mi{\\l}kowski, Piotr  and\n      Za{\\'s}ko-Zieli{\\'n}ska, Monika\",\n    booktitle = \"Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)\",\n    month = nov,\n    year = \"2019\",\n    address = \"Hong Kong, China\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/K19-1092\",\n    doi = \"10.18653/v1/K19-1092\",\n    pages = \"980--991\",\n    abstract = \"In this article we present an extended version of PolEmo {--} a corpus of consumer reviews from 4 domains: medicine, hotels, products and school. Current version (PolEmo 2.0) contains 8,216 reviews having 57,466 sentences. Each text and sentence was manually annotated with sentiment in 2+1 scheme, which gives a total of 197,046 annotations. We obtained a high value of Positive Specific Agreement, which is 0.91 for texts and 0.88 for sentences. PolEmo 2.0 is publicly available under a Creative Commons copyright license. We explored recent deep learning approaches for the recognition of sentiment, such as Bi-directional Long Short-Term Memory (BiLSTM) and Bidirectional Encoder Representations from Transformers (BERT).\",\n}",
 "signal": "permissive",
 "reason": "The declared licence (cc-by-sa-4.0) is classified as share-alike."
}