Automatic Sarcasm Detection: A Survey <s> 73:4 <s> According to the mention theory of irony put forward by Sperber and Wilson and tested by Jprgensen, Miller, and Sperber, verbal ironies are implicit echoic mentions of meaning conveying a derogatory attitude to the meaning mentioned. In their criticisms, Clark and Gerrig misrepresent mention theory. The pretense theory, which they offer as a superior alternative, might provide a plausible description of parody, but it fails to account for many types and many properties of irony proper. <s> BIB001 </s> Automatic Sarcasm Detection: A Survey <s> 73:4 <s> In this article, irony is viewed as a mode of indirect negation. Based on this view, interpreting irony does not involve canceling the indirectly negated message and replacing it with the implicated one (as contended by, e.g., Clark & Gerrig, 1984; Grice, 1975). Rather, irony understanding involves processing both the negated and implicated messages, so that the difference between them may be computed. This view thus differs from the view which assumes that irony involves only one interpretation (e.g., Gibbs, 1986a; Sperber & Wilson, 1981; Wilson & Sperber, 1992). Holding that irony activates both the literal/explicit and the ironic/implicated meanings predicts that irony will be more difficult to understand than a nonironic use of the same utterance. Reanalysis of previous findings (Gibbs, 1986a) evinces that irony takes longer to process than nonironic use of the same utterance. Though irony is more difficult to understand than nonironic language, speakers apply this mode for certain communicative goals... <s> BIB002 </s> Automatic Sarcasm Detection: A Survey <s> 73:4 <s> Sentiment Analysis is a technique to identify people's opinion, attitude, sentiment, and emotion towards any specific target such as individuals, events, topics, product, organizations, services etc. Sarcasm is a special kind of sentiment that comprise of words which mean the opposite of what you really want to say (especially in order to insult or wit someone, to show irritation, or to be funny). People often expressed it verbally through the use of heavy tonal stress and certain gestural clues like rolling of the eyes. These tonal and gestural clues are obviously not available for expressing sarcasm in text, making its detection reliant upon other factors. In this paper, two approaches to detect sarcasm in the text of Twitter data were proposed. The first is a parsing-based lexicon generation algorithm (PBLGA) and the second was to detect sarcasm based on the occurrence of the interjection word. The combination of two approaches is also shown and compared with the existing state-of-the-art approach to detect sarcasm. First approach attains a 0.89, 0.81 and 0.84 precision, recall and f -- score respectively. Second approach attains 0.85, 0.96 and 0.90 precision, recall and f -- score respectively in tweets with sarcastic hashtag. <s> BIB003
A. Joshi et al. (4) Echoic mention theory: A contrary view is described in Reference BIB001 . The theory states that a literal proposition may not always be intended. This can be understood with the help of the sentence "I love it when I do not forward a chain mail and I die the next day." The intention of the speaker is to remind the listener of situations where chain mails do not have any result. It is through highlighting this fact that the speaker's intended ridicule of chain mails is understood. The echoic reminder theory also offers a similar perspective  . The echoic reminder theory states that a sarcastic statement reminds the listener of a situation they have encountered but with clues to indicate the sarcasm. For example, the sentence "Visits to a dentist are fun" reminds the listener of the situation of visiting a dentist and the popular appraisal that it is an unpleasant event. (5) Sarcasm as a dropped negation: Reference BIB002 states that irony/sarcasm is a form of negation in which an explicit negation marker is lacking. In other words, when one expresses sarcasm, a negation is intended, despite the lack of a negation word like "not." For example, the sarcastic sentence "Being awake at 4 am with a headache is fun" is equivalent to the non-sarcastic sentence "Being awake at 4 am with a headache is not fun." This results in the possibility that many sarcastic sentences could be converted to non-sarcastic by simply applying an appropriate negation. (6) Understanding sarcasm: Reference  describe how sarcasm may be understood. The authors state that violation of truthfulness maxims is a key for a listener to understand sarcasm. For example, "I love being ignored" is understood as sarcastic by a listener who believes that being ignored is not a pleasant state to be in. However, "I love your new shirt!" may or may not be sarcastic. The intended sarcasm cannot be understood until the listener observes that the literal meaning of the text violates truthfulness. To understand sarcasm, if any, in the sentence above, it would be essential to know information that would violate the truthfulness. Some of these linguistic theories see a close correspondence with advances in automatic sarcasm detection. For example, the additional "information" that is said to be necessary to violate truthfulness, is essentially the different forms of contextual information that automatic sarcasm detection aims to capture. In general, sarcasm is a verbal irony that has an intention to be mocking/ridiculing towards an entity. However, what context is required for the sarcasm to be understood forms a crucial component. Compare the sarcastic example "I love being ignored" with another "I love solving math problems all day." The former is likely to be sarcastic for all speakers. The latter is likely to be sarcastic for most speakers. However, for authors who do really enjoy math, the statement is not sarcastic. The sarcasm in the latter may be conveyed through an author's context or paralinguistic cues (as in the case of illocutionary sarcasm). Thus, sarcasm understanding and automatic sarcasm detection are contingent on what information (or context) is known. In general, sarcasm can be summarized by a definition by Reference  , which states that sarcasm is "a deliberate attempt to point out, question, or ridicule attitudes and beliefs by the use of words and gestures in ways that run counter to their normal meanings." This definition has multiple components. The first is that sarcasm is "deliberate," which means that it is purposefully intended by the speaker and not an interpretation of the listener. That sarcasm "points out, questions, or ridicules" means that there is an implied negative sentiment. For example, if a teacher catches a student cheating on a test and says, "Your parents would be really proud today," the implied negative sentiment is towards the listener (the student). The last part of the definition, "in ways that run counter to their normal meanings" highlights the relationship of sarcasm with irony. Irony is a situation in which something that was intended to have a particular result has the opposite or a very different result. BIB003 Thus, sarcasm consists of: (i) the use of irony and (ii) the presence of ridicule. Based on the theories described here, understanding sarcasm (by humans or through programs) can be divided into the following components: (1) Identification of shared knowledge: The sentence "I love being ignored" cannot be understood as sarcastic without the shared knowledge that people do not like being ignored. This specifically holds true in case of specific context. For example, the sentence "I love solving math problems all weekend" may be perceived as non-sarcastic by a listener who loves math or by a listener who knows that the speaker loves math. A listener, in these situations, would either look for a dropped negation or an echoic reminder, as given by theories above. (2) Identification of what constitutes ridicule: As seen in the linguistic studies, the ridicule may be conveyed through different reactions such as laughter, change of topic, and so on.