@inproceedings{RuppenhoferSteinerWiegand2019,
  author    = {Josef Ruppenhofer and Petra Steiner and Michael Wiegand},
  title     = {Evaluating the Morphological Compositionality of Polarity},
  series = {Proceedings of the 11th International Conference on Recent Advances in Natural Language Processing, RANLP 2017, Varna, Bulgaria, 2-8 September, 2017},
  editor    = {Galia Angelova and Kalina Bontcheva and Ruslan Mitkov and Ivelina Nikolova and Irina Temnikova},
  publisher = {Incoma Ltd.},
  address   = {Shoumen},
  isbn      = {978-954-452-049-6},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-84917},
  pages     = {625 -- 633},
  year      = {2019},
  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.},
  language  = {en}
}