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In:Recent Advances in Multiword Units in Machine Translation and Translation Technology
Edited by Johanna Monti, Gloria Corpas Pastor, Ruslan Mitkov and Carlos Manuel Hidalgo-Ternero
[Current Issues in Linguistic Theory 366] 2024
► pp. 197–217

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Chapter 11
Irony in American-English tweets

A cognitive and phraseological analysis

 | Universidad Complutense de Madrid
Published online: 7 November 2024
DOI logo with link
https://doi.org/10.1075/cilt.366.11mar
Abstract
The present study examines verbal irony from a cognitive linguistics perspective, based on Ruiz de Mendoza’s (2017) development of the echoic account and on big data. Built on previous research on the detection of Spanish ironic utterances in Twitter (Martín-Gascón, 2019), this investigation aims to analyze how American-English speakers conceptualize and express irony and compares findings to the Spanish ones. The dataset, initially consisting of 1,157,773,379 tweets from 248 countries and 66 languages, was first reduced to 27,517 tweets from English-speaking users in the United States using the words “irony”, “ironies”, and “ironic”, then to 605 containing the words as hashtag and finally to 495 tweets evincing implicit and explicit-echoic irony. An in-depth cognitive and qualitative analysis of the sample revealed the complexities of perceiving irony in written discourse and, therefore, the relevance of adding contextual ironic markers, such as hashtags, emojis, interjections, laughter typing and ironic phraseology, among others. In line with Martín-Gascón’s (2019) study, findings showed a higher use of positive and explicit-echoic irony as compared to implicit and negative irony. By drawing attention to the similarities and differences in the expression of irony, we expect to offer preliminary informed options for the design of pedagogical proposals that enhance not only the learners’ linguistic and ironic competencies, but also their intercultural awareness.
Article outline
  • 1.Introduction
  • 2.Theoretical background
    • 2.1Verbal irony: An understudied figure of speech
    • 2.2Irony detection in Twitter: An arduous task for users and researchers
  • 3.Methodology
  • 4.Results and discussion
    • 4.1(RQ1) Do English-speaking users of Twitter conceptualize and use VI appropriately?
    • 4.2(RQ2) How is irony conveyed, through explicit or non-explicit echo? Are the ironic statements positive or negative?
    • 4.3(RQ3) Do English and Spanish-speaking users conceptualize and express irony in a similar manner? Or does it differ cross-linguistically?
    • 4.4(RQ4) Do English and Spanish-speaking users ironize about the same topics?
  • 5.Conclusions
  • Notes
  • References
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