Irony and sarcasm in advertisements: Effects of relevant inappropriateness

Lagerwerf, Leny

doi:10.1016/j.pragma.2007.05.002

Cited by 41 publications

(33 citation statements)

References 25 publications

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“…e approach attained an accuracy of 85.03%. Lagerwerf [29] developed a system to detect irony and sarcasm from advertisements and public announcements. AL-Sharuee et al [30] developed a system for sentiment analysis using contextual analysis and unsupervised ensemble learning in order to handle domain-dependency problem.…”

Section: Literature Survey On Sarcasm Detectionmentioning

confidence: 99%

Multi-Rule Based Ensemble Feature Selection Model for Sarcasm Type Detection in Twitter

Sundararajan

Palanisamy

2020

Computational Intelligence and Neuroscience

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Sentimental analysis aims at inferring how people express their opinion over any piece of text or topic of interest. This article deals with detection of an implicit form of the sentiment, referred to as sarcasm. Sarcasm conveys the opposite of what people try to convey in order to criticize or ridicule in a humorous way. It plays a vital role in social networks since most of the tweets or posts contain sarcastic nuances. Existing approaches towards the study of sarcasm deals only with the detection of sarcasm. In this paper, in addition to detecting sarcasm from text, an approach has been proposed to identify the type of sarcasm. The main motivation behind determining the types of sarcasm is to identify the level of hurt or the true intent behind the sarcastic text. The proposed work aims to improve upon the existing approaches by incorporating a new perspective which classifies the sarcasm based on the level of harshness employed. The major application of the proposed work would be relating the emotional state of a person to the type of sarcasm exhibited by him/her which could provide major insights about the emotional behavior of a person. An ensemble-based feature selection method has been proposed for identifying the optimal set of features needed to detect sarcasm from tweets. This optimal set of features was employed to detect whether the tweet is sarcastic or not. After detecting sarcastic sentences, a multi-rule based approach has been proposed to determine the type of sarcasm. As an initial attempt, sarcasm has been classified into four types, namely, polite sarcasm, rude sarcasm, raging sarcasm, and deadpan sarcasm. The performance and efficiency of the proposed approach has been experimentally analyzed, and change in mood of a person for each sarcastic type has been modelled. The overall accuracy of the proposed ensemble feature selection algorithm for sarcasm detection is around 92.7%, and the proposed multi-rule approach for sarcastic type identification achieves an accuracy of 95.98%, 96.20%, 99.79%, and 86.61% for polite, rude, raging, and deadpan types of sarcasm, respectively.

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Section: Literature Survey On Sarcasm Detectionmentioning

confidence: 99%

Multi-Rule Based Ensemble Feature Selection Model for Sarcasm Type Detection in Twitter

Sundararajan

Palanisamy

2020

Computational Intelligence and Neuroscience

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“…The unexpected outcome in the form of a warning against an "extremely delicious" product makes the advert boldly humorous. Lagerwerf (2007Lagerwerf ( , p.1703 in a similar sense claims: "The effort people may have to come up with for a correct interpretation will result in their appreciating the trope, and hence the advertisement itself. "…”

Section: Other Genres In Advertsmentioning

confidence: 99%

Multigeneric Intertextuality in Advertising: Discourse Strategy from a Cognitive Perspective

Nemčoková

2014

Topics in Linguistics

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Advert recipients have wide-ranging experiences of perceiving other texts. When these experiences become the basis of perceiving advert messages, we speak of intertextuality operating as a discourse strategy. This paper studies multigeneric intertextuality in printed advertising, i.e. delivering an advert message through a register or text-form typical of other genres, for which discourse analysis and the genre studies perspective are adapted. From the cognitive linguistics perspective, it focuses on how the experience becomes the basis of building an emotive and attitudinal layer of meaning via exploring the recipient's mental space. The article studies cues signalling intertextual processing, specifically cues of socially determined discourses such as cooking recipes, warning signs, computer-mediated communication, scientific discussions or travel brochures, which may function as mental space inducing cues in the collected adverts. It also deals with how intertextuality in adverts can be scaled and how the level of explicitness relates to promoting various categories of products.

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“…Burgers et al, 2012a;Lagerwerf, 2007;Van Mulken et al, 2011): een ironische uiting fungeert als een soort raadsel. Als de ontvanger dit raadsel uiteindelijk oplost, geeft dit plezier waardoor de kans groter is dat de lezer ook de boodschap accepteert.…”

Section: Communicatieve Doelen Van Ironieunclassified

Het ironisch spectrum - Een overzicht van onderzoek naar het begrip en de retorische effecten van verbale ironie

Burgers¹,

Mulken²

2013

Tijdschrift Voor Taalbeheersing

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Verbal irony has been studied in various academic disciplines such as linguistics, pragmatics, communication science and social psychology. However, due to the multidisciplinarity of the respective fields, each of these disciplines has developed its own irony literature. This paper discusses the current state of affairs of research into comprehension and rhetorical effects of verbal irony, with an emphasis on pragmatic aspects of irony. We propose our model of the ironic spectrum based on predictors related to (1) the formulation of the ironic utterance, (2) the co-text of the ironic utterance and (3) the context of the ironic utterance. This model integrates linguistic, pragmatic, communication-scientific and social-psychological evidence on the comprehension and effectiveness of verbal irony.

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Irony and sarcasm in advertisements: Effects of relevant inappropriateness

Cited by 41 publications

References 25 publications

Multi-Rule Based Ensemble Feature Selection Model for Sarcasm Type Detection in Twitter

Multi-Rule Based Ensemble Feature Selection Model for Sarcasm Type Detection in Twitter

Multigeneric Intertextuality in Advertising: Discourse Strategy from a Cognitive Perspective

Het ironisch spectrum - Een overzicht van onderzoek naar het begrip en de retorische effecten van verbale ironie

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