@inproceedings{ahuja-etal-2018-makes,
    title = "What makes us laugh? Investigations into Automatic Humor Classification",
    author = "Ahuja, Vikram  and
      Bali, Taradheesh  and
      Singh, Navjyoti",
    editor = "Nissim, Malvina  and
      Patti, Viviana  and
      Plank, Barbara  and
      Wagner, Claudia",
    booktitle = "Proceedings of the Second Workshop on Computational Modeling of People{'}s Opinions, Personality, and Emotions in Social Media",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W18-1101/",
    doi = "10.18653/v1/W18-1101",
    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."
}