@InProceedings{ruppenhofer-steiner-wiegand:2017:RANLP,
  author    = {Ruppenhofer, Josef  and  Steiner, Petra  and  Wiegand, Michael},
  title     = {Evaluating the morphological compositionality of polarity},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  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.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_081}
}