@inproceedings{WiegandSchulderRuppenhofer2016,
  author    = {Michael Wiegand and Marc Schulder and Josef Ruppenhofer},
  title     = {Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features},
  series = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  editor    = {Kevin Knight and Ani Nenkova and Owen Rambow},
  publisher = {Association for Computational Linguistics},
  address   = {San Diego (California)},
  isbn      = {978-1-941643-91-4},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-55113},
  pages     = {778 -- 788},
  year      = {2016},
  abstract  = {We examine different features and classifiers for the categorization of opinion words into actor and speaker view. To our knowledge, this is the first comprehensive work to address sentiment views on the word level taking into consideration opinion verbs, nouns and adjectives. We consider many high-level features requiring only few labeled training data. A detailed feature analysis produces linguistic insights into the nature of sentiment views. We also examine how far global constraints between different opinion words help to increase classification performance. Finally, we show that our (prior) word-level annotation correlates with contextual sentiment views.},
  language  = {en}
}