@inproceedings{barnes-etal-2019-lexicon,
    title = "Lexicon information in neural sentiment analysis: a multi-task learning approach",
    author = "Barnes, Jeremy  and
      Touileb, Samia  and
      {\O}vrelid, Lilja  and
      Velldal, Erik",
    editor = "Hartmann, Mareike  and
      Plank, Barbara",
    booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
    month = sep # "–" # oct,
    year = "2019",
    address = "Turku, Finland",
    publisher = {Link{\"o}ping University Electronic Press},
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W19-6119/",
    pages = "175--186",
    abstract = "This paper explores the use of multi-task learning (MTL) for incorporating external knowledge in neural models. Specifically, we show how MTL can enable a BiLSTM sentiment classifier to incorporate information from sentiment lexicons. Our MTL set-up is shown to improve model performance (compared to a single-task set-up) on both English and Norwegian sentence-level sentiment datasets. The paper also introduces a new sentiment lexicon for Norwegian."
}