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Presupposition contributions in stand-up comedy (discourse analysis of Raditya Dika’s stand-up comedy on YouTube)

Authors: Faisal Fahdian Puksi;

Presupposition contributions in stand-up comedy (discourse analysis of Raditya Dika’s stand-up comedy on YouTube)

Abstract

This study aims to find out how a comic establishes strategy through presupposition in contributing to building a humour effect in stand-up comedy. A qualitative descriptive method was employed in this research to get full and depth conception. 15 stand-up comedy videos hosted by Raditya Dika on YouTube are used in this research. All data obtained then transcribed which then selected 60 statements that considered representing the entire transcript data. From 60 statements, it can be found 651 presuppositions that contribute to building the effects of humour. Presupposition contribution in constructing the effects of humour lies at the level of cognitive process, semantic mechanism, and contextual speech. At the cognitive process level, the researcher finds that presupposition will contribute in creating humour if in a statement there is a presupposition with different and conflicting perspectives. At the semantic mechanism level, the presuppositions of the latter sentence can produce humour by relying on the reference to the previous sentence. For the contextual speech, presupposition will contribute to the creation of humour if it violates the conversational maxim.

Keywords

comic Raditya Dika, presupposition, stand-up comedy, Language and Literature, P, P1-1091, Philology. Linguistics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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