Sarcasm Detection Using Grice ’ s Maxims

S is of interest to researchers because of its ambiguous nature—sarcasm research can provide insight into how we use different types of linguistic and extralinguistic information to process ambiguous language of many types (Rockwell, 2005). We can also use knowledge about how sarcasm functions in conversation to inform our understanding of pragmatic language difficulties present in people with particular brain injuries or developmental disabilities, such as Autism Spectrum Disorders or Specific Language Impairment (Ryder & Leinonen, 2014; Surian, Baron-Cohen, & Van der Lely, 1996). For example, determining which kinds of information people typically use to detect sarcasm can help practitioners assist patients with pragmatic difficulties in identifying and interpreting nonliteral speech. Constructing a complete explanatory theory of sarcasm interpretation has been a source of controversy since Grice’s foundational 1975 paper, “Logic and Conversation,” which proposes that conversational partners assume one another to be acting cooperatively within the current speech exchange, and thus often interpret an apparent breach of conversational protocol as an indirect way of implying something which has not actually been said. Two major countertheories emerged soon after—Mention Theory and Pretense Theory—with criticisms of Grice and new ways to conceive of sarcastic utterances altogether. Both theories posit that only the literal meaning of the utterance is represented, and the speaker’s attitude toward the utterance is indicated by other methods. These single-meaning models differ from Grice’s in that they eliminate the need for an inferred “inverted” meaning of the utterance.  While these theories emphasize the interpretation of sarcasm, more recent sarcasm research focuses on sarcasm detection, specifically which kinds of information hearers utilize when determining whether a given utterance is sarcastic. For instance, while vocal and visual cues may be available to hearers for sarcasm detection in a face-to-face conversation, contextual and lexical cues may become more important in written language. Couched in Gricean terms and expanding upon previous research on sarcasm cues, I propose a particular set of sarcasm cues that rely on an additional violation of Grice’s maxims as a way of directing a conversational partner’s attention to the nonliteral nature of a sarcastic utterance. In order to test the validity of these maxim-violation cues, a set of tweets was compiled, half of which were sarcastic and half of which were intended literally. Half of each of those groups contained maxim-violation cues, while half did not. The use of tweets as the source of the utterances was intended to target language which did not make use of more well-studied sarcasm cues such as body language, intonation, and, for the most part, conversational context. Participants were asked whether each of the tweets was sarcastic. Participants also recorded how certain they were of their sarcasm detection for each tweet, providing a built-in tool to disregard noise in the data due to random guesses. The presence of maxim-violation cues predicted a statistically significant amount of variance in sarcasm detection. The effect of sarcastic intent on sarcasm detection was also statistically significant, suggesting that other content-based cues (aside from maxim-violation cues) come into play even in written language with little context. This paper will be organized as follows: Section 1 will establish a theoretical framework within which to analyze sarcasm detection; section 2 will introduce the concepts of sarcasm detection