@InProceedings{ahuja-bali-singh:2018:W18-11,
  author    = {Ahuja, Vikram  and  Bali, Taradheesh  and  Singh, Navjyoti},
  title     = {What makes us laugh? Investigations into Automatic Humor Classification},
  booktitle = {Proceedings of the Second Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1--9},
  abstract  = {Most scholarly works in the field of computational detection of humour derive their inspiration from the incongruity theory. Incongruity is an indispensable facet in drawing a line between humorous and non-humorous occurrences but is immensely inadequate in shedding light on what actually made the particular occurrence a funny one. Classical theories like Script-based Semantic Theory of Humour and General Verbal Theory of Humour try and achieve this feat to an adequate extent. In this paper we adhere to a more holistic approach towards classification of humour based on these classical theories with a few improvements and revisions. Through experiments based on our linear approach and performed on large data-sets of jokes, we are able to demonstrate the adaptability and show componentizability of our model, and that a host of classification techniques can be used to overcome the challenging problem of distinguishing between various categories and sub-categories of jokes.},
  url       = {http://www.aclweb.org/anthology/W18-1101}
}