@inproceedings{RuppenhoferBrandesSteineretal.2016,
  author    = {Josef Ruppenhofer and Jasper Brandes and Petra Steiner and Michael Wiegand},
  title     = {Ordering adverbs by their scaling effect on adjective intensity},
  series = {International Conference Recent Advances in Natural Language Processing},
  publisher = {INCOMA Ltd.},
  address   = {Shoumen},
  issn      = {1313-8502},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-52052},
  pages     = {545 -- 554},
  year      = {2016},
  abstract  = {In recent years, theoretical and computational linguistics has paid much attention to linguistic items that form scales. In NLP, much research has focused on ordering adjectives by intensity (tiny < small). Here, we address the task of automatically ordering English adverbs by their intensifying or diminishing effect on adjectives (e.g. extremely small < very small). We experiment with 4 different methods: 1) using the association strength between adverbs and adjectives; 2) exploiting scalar patterns (such as not only X but Y); 3) using the metadata of product reviews; 4) clustering. The method that performs best is based on the use of metadata and ranks adverbs by their scaling factor relative to unmodified adjectives.},
  language  = {en}
}