@InProceedings{bali-singh:2016:PEOPLES,
  author    = {Bali, Taradheesh  and  Singh, Navjyoti},
  title     = {Sarcasm Detection : Building a Contextual Hierarchy},
  booktitle = {Proceedings of the Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {119--127},
  abstract  = {The conundrum of understanding and classifying sarcasm has been dealt with by
	the traditional theorists as an analysis of a sarcastic utterance and the
	ironic situation that surrounds it. The problem with such an approach is that
	it is too narrow, as it is unable to sufficiently utilize the two indispensable
	agents in making such an utterance, viz. the speaker and the listener. It
	undermines the necessary context required to comprehend a sarcastic utterance.
	In this paper, we propose a novel approach towards understanding sarcasm in
	terms of the existing knowledge hierarchy between the two participants, which
	forms the basis of the context that both agents share. The difference in
	relationship of the speaker of the sarcastic utterance and the disparate
	audience found on social media, such as Twitter, is also captured. We then
	apply our model on a corpus of tweets to achieve significant results and
	consequently, shed light on subjective nature of context, which is contingent
	on the relation between the speaker and the listener.},
  url       = {http://aclweb.org/anthology/W16-4313}
}