@inproceedings{WiegandRuppenhofer2016,
  author    = {Michael Wiegand and Josef Ruppenhofer},
  title     = {Opinion Holder and Target Extraction based on the Induction of Verbal Categories},
  series = {Proceedings of the 19th Conference on Computational Language Learnung, Beijing China, July 30-31, 2015},
  publisher = {Association for Computational Linguistics},
  isbn      = {978-1-941643-77-8},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-52305},
  pages     = {215 -- 225},
  year      = {2016},
  abstract  = {We present an approach for opinion role induction for verbal predicates. Our model rests on the assumption that opinion verbs can be divided into three different types where each type is associated with a characteristic mapping between semantic roles and opinion holders and targets. In several experiments, we demonstrate the relevance of those three categories for the task. We show that verbs can easily be categorized with semi-supervised graphbased clustering and some appropriate similarity metric. The seeds are obtained through linguistic diagnostics. We evaluate our approach against a new manually-compiled opinion role lexicon and perform in-context classification.},
  language  = {en}
}