@InProceedings{kper-schulteimwalde:2018:N18-2,
  author    = {Köper, Maximilian  and  Schulte im Walde, Sabine},
  title     = {Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {150--156},
  abstract  = {We present a computational model to detect and distinguish analogies in meaning shifts between German base and complex verbs. In contrast to corpus-based studies, a novel dataset demonstrates that “regular” shifts represent the smallest class. Classification experiments relying on a standard similarity model successfully distinguish between four types of shifts, with verb classes boosting the performance, and affective features for abstractness, emotion and sentiment representing the most salient indicators.},
  url       = {http://www.aclweb.org/anthology/N18-2024}
}