Completion Date
8-2017
Document Type
Thesis
Degree Name
Master of Science (MS)
Program or Discipline Name
Computer Science
First Advisor
Nushwan Al-Nakash, PhD.
Abstract
Humor is a very complex characteristic concept that defines us as human beings and social entities. Humor is an essential component in personal communication. How to create a method or model to discover the structures behind humor, recognize humor and even extraction of humor remains a challenge because of its subjective nature. Humor also provides valuable information related to linguistic, psychological, neurological and sociological phenomena. However, because of its complexity, humor is still an undefined phenomenon. Because the reaction that make people laugh can hardly be generalized or formalized. For instance, cognitive aspects as well as cultural knowledge, are some of the multi-factorial variables that should be analyzed in order to understand humor's properties.
Although it is impossible to understand universal humor characteristics, one can still capture the possible latent structures behind humor. In my work, I will try to uncover several latent semantic structures behind humor, in terms of meaning incongruity, ambiguity, phonetic style and personal affect. In addition to humor recognition, identifying anchors, or which words prompt humor in a sentence, is essential in understanding the phenomenon of humor in language.
Proposed technique is created using the concepts of linguistics and it has significant accuracy of over 70+% compared to 23.06% of Word Index power method.
Recommended Citation
Jain, M. (2017). Humor Detection. Retrieved from https://digitalcommons.harrisburgu.edu/csms_dandt/1