@inproceedings{kocon-etal-2019-multi-level,
    title = "Multi-level analysis and recognition of the text sentiment on the example of consumer opinions",
    author = "Koco{\'n}, Jan  and
      Za{\'s}ko-Zieli{\'n}ska, Monika  and
      Mi{\l}kowski, Piotr",
    editor = "Mitkov, Ruslan  and
      Angelova, Galia",
    booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
    month = sep,
    year = "2019",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/ingest_wac_2008/R19-1066/",
    doi = "10.26615/978-954-452-056-4_066",
    pages = "559--567",
    abstract = "In this article, we present a novel multi-domain dataset of Polish text reviews, annotated with sentiment on different levels: sentences and the whole documents. The annotation was made by linguists in a 2+1 scheme (with inter-annotator agreement analysis). We present a preliminary approach to the classification of labelled data using logistic regression, bidirectional long short-term memory recurrent neural networks (BiLSTM) and bidirectional encoder representations from transformers (BERT)."
}