2026-07-11T19:15:51Zhttps://clarin-pl.eu/oai/request

oai:clarin-pl.eu:11321/7102022-03-17T16:25:23Zhdl_11321_3hdl_11321_4

PolEmo 2.0 Sentiment Analysis Dataset for CoNLL Kocoń, Jan Zaśko-Zielińska, Monika Miłkowski, Piotr sentiment analysis Polish consumer reviews PolEmo 2.0: Corpus of Multi-Domain Consumer Reviews, evaluation data for article presented at CoNLL Citation: @inproceedings{kocon-etal-2019-multi, title = "Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews", author = "Koco{\'n}, Jan and Mi{\l}kowski, Piotr and Za{\'s}ko-Zieli{\'n}ska, Monika", booktitle = "Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/K19-1092", doi = "10.18653/v1/K19-1092", pages = "980--991", 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).", } 2019-09-19 corpus http://hdl.handle.net/11321/710 pol Creative Commons - Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ CC text/plain; charset=utf-8 application/zip application/octet-stream application/zip application/zip downloadable_files_count: 4 Wrocław University of Science and Technology