@inproceedings{ruppenhofer-etal-2017-evaluating,
    title = "Evaluating the morphological compositionality of polarity",
    author = "Ruppenhofer, Josef  and
      Steiner, Petra  and
      Wiegand, Michael",
    editor = "Mitkov, Ruslan  and
      Angelova, Galia",
    booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing, {RANLP} 2017",
    month = sep,
    year = "2017",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/fix-sig-urls/R17-1081/",
    doi = "10.26615/978-954-452-049-6_081",
    pages = "625--633",
    abstract = "Unknown words are a challenge for any NLP task, including sentiment analysis. Here, we evaluate the extent to which sentiment polarity of complex words can be predicted based on their morphological make-up. We do this on German as it has very productive processes of derivation and compounding and many German hapax words, which are likely to bear sentiment, are morphologically complex. We present results of supervised classification experiments on new datasets with morphological parses and polarity annotations."
}