References
Alba-Juez, L., & Attardo, S. (2014). The
evaluative palette of VI. In G. Thompson & L. Alba-Juez (Eds.), Evaluation
in
context (pp. 93–116). John Benjamins.
Attardo, S. (2000). Irony
markers and functions: Towards a goal-oriented theory of irony and its
processing. Rask – International Journal of Language and
Communication 12 (1), 3–20.
Attardo, S., Eisterhold, J., Hay, J., & Poggi, I. (2003). Multimodal
markers of irony and sarcasm. Humor – International Journal of Humor
Research, 16(2), 243–260. .
Baquero, A., & Mitkov, R. (2017). Translation
memory systems have a long way to go. Proceedings of the Workshop
Human-Informed Translation and Interpreting
Technology (pp. 44–51).
Barcelona, A. (Ed.). (2000). Metaphor
and metonymy at the crossroads. Mouton de Gruyter.
Becker, I., & Giora, R. (2018). The
defaultness hypothesis: A quantitative corpus-based study of non/default sarcasm and literalness
production. Journal of
Pragmatics, 138, 149–164. .
Bryant, G. A. (2010). Prosodic
contrasts in ironic speech. Discourse
Processes, 47(7), 545–566.
Chowdhary, K. R. (2020). Fundamentals
of artificial intelligence. Springer.
Cignarella, A. T., Frenda, S., Basile, V., Bosco, C., Patti, V., & Rosso, P. (2018). Overview
of the evalita 2018 task on irony detection in Italian tweets (ironita). Sixth
Evaluation Campaign of Natural Language Processing and Speech Tools for Italian (EVALITA
2018) (Vol.
2263) 1–6. CEUR-WS.
Colston, H. (1997). “I’ve
never seen anything like it”: Overstatement, understatement, and
irony. Metaphor
Symbol, 12(1), 43–58.
Corpas Pastor, G. (1996). Manual de fraseología
Española. Gredos.
Corpas Pastor, G. (2003). Diez años de investigación en fraseología: Análisis sintáctico-semánticos, contrastivos y
traductológicos. Iberoamericana.
Corpas Pastor, G. (2013a). All
that glitters is not gold when translating phraseological
units. In J. Monti, R. Mitkov, G. Corpas Pastor & V. Seretan (Eds.) Workshop
proceedings for multi-word units in machine translation and translation
technologies (pp. 9–10). The
European Association for Machine Translation.
Corpas Pastor, G. (2013b). Detección, descripción y contraste de las unidades fraseológicas mediante
tecnologías lingüísticas. In I. Olza & E. Manero (Eds.), Fraseopragmática (pp. 335–373). Frank & Timme.
Coulson, S. (2005). Sarcasm
and the space structuring model. In S. Coulson & B. Lewandowska-Tomasczyk (Eds.), The
literal and nonliteral in language and
thought (pp. 129–144). Peter Lang.
Dirven, R. (1993). Metonymy
and metaphor: Different mental strategies of conceptualisation. Leuvense
Bijdragen. 82, 1–25.
Farzindar, A., & Inkpen, D. (2015). Natural
language processing for social media. Synthesis Lectures on Human Language
Technologies, 8(2), 1–166.
Fauconnier, G., & Turner, M. (2002). The
way we think. Conceptual blending and the mind’s hidden complexities. New York: Basic Books.
Frenda, S. (2017). Ironic
gestures and tones on Twitter. 4th Italian Conference on
Computational Linguistics, CLiC-it 2017 (Vol.
2006, pp. 1–6). CEUR-Workshop.
Gibbs, R. W. (2007). Irony
among friends. In R. W. Gibbs & H. L. Colston (Eds.). Irony
in language and thought: A cognitive science
reader (pp. 339–360). Lawrence Erlbaum.
Gibbs, R. W., & Colston, H. L. (2012). Interpreting
figurative meaning. Cambridge University Press.
Giora, R., & Becker, I. (2019) S/he
is not the most sparkling drink in the pub. Global vs. local cue – Which reigns
supreme? Metaphor and
Symbol, 34(3), 141–157.
Giora, R., Federman, S., Kehat, A., Fein, O., & Sabah, H. (2005). Irony
aptness. Humor, 18(1), 23–39.
Giora, R., Givoni, S., & Fein, O. (2015). Defaultness
reigns: The case of sarcasm. Metaphor
Symbol, 30(4), 290–313.
Giora, R., Livnat, E., Fein, O., Barnea, A., Zeiman, R., & Berger, I. (2013). Negation
generates nonliteral interpretations by default. Metaphor and
Symbol, 28(2), 89–115.
Haiman, J. (1998). Talk
is cheap: Sarcasm, alienation, and the evolution of language. Oxford University Press on Demand.
Herbert, C. & Gerrig, R. (2007). On
the pretense theory of irony. Irony in language and thought: A cognitive
science reader, 25–33.
Jia, X., Deng, Z., Min, F., & Liu, D. (2019). Three-way
decisions-based feature fusion for Chinese irony detection. International
Journal of Approximate
Reasoning, 113, 324–335.
Joshi, A., Sharma, V., & Bhattacharyya, P. (2015). Harnessing
context incongruity for sarcasm detection. Proceedings of the 53rd
Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference
on Natural Language Processing (Volume 2: Short
Papers) (pp. 757–762). ACS.
Joshi, A., Bhattacharyya, P., & Carman, M. J. (2017). Automatic
sarcasm detection: A survey. ACM Computing Surveys
(CSUR), 73, 1–22.
Karoui, J., Benamara, F., Moriceau, V., Patti, V., Bosco, C., & Aussenac-Gilles, N. (2017). Exploring
the impact of pragmatic phenomena on irony detection in tweets: A multilingual corpus
study. 15th Conference of the European Chapter of the
Association for Computational
Linguistics (pp. 262–272). ACL.
Kövecses, Z. (2000). The
scope of metaphor. In A. Barcelona (Ed.). Metaphor
and metonymy at the crossroads: A cognitive
perspective (pp. 79–92). Mouton de Gruyter.
Kreuz, R. J. (2000). The
production and processing of VI. Metaphor and
Symbol, 15(1–2), 99–107.
Lakoff, G., & Johnson, M. (1980). Metaphors
we live by. University of Chicago Press.
Maroto, A. (2019a). Big
data, Twitter and music: New paths in research. [URL]. [14th March 2019].
Maroto, A. (2019b). El metadiscurso en las redes sociales: Una extensión
multidimensional. Análisis de cinco dirigentes políticos de la
coalición Ahora Podemos a través de la red social Twitter. [URL]. [3rd April 2024].
Martín-Gascón, B. (2019). A
cognitive modeling approach on ironical phraseology in
Twitter. In G. Corpas & R. Mitkov (Eds.). Computational
and corpus-based
phraseology (pp. 299–314). Springer, Cham.
Martín-Gascón, B. (2023). La enseñanza de la ironía en la clase de Español/L2: un estudio empírico con estudiantes de
nivel intermedio y avanzado. Porta Linguarum Revista
Interuniversitaria De Didáctica De Las Lenguas
Extranjeras, (39), 213–230.
Muecke, D. C. (1978). Irony
markers. Poetics, 7(4), 363–375.
Rosenthal, S., Farra, N., & Nakov, P. (2017). SemEval-2017
task 4: Sentiment analysis in Twitter. Proceedings of the 11th International
Workshop on Semantic
Evaluation (pp. 502–518).
Rozental, A., & Fleischer, D. (2017). Amobee
at SemEval-2017 Task 4: Deep learning system for sentiment detection on
Twitter. Proceedings of the 11th International Workshop on Semantic
Evaluation (pp. 652–657).
Ruiz de Mendoza, F. J. (2014). On
the nature and scope of metonymy in linguistic description and explanation: towards settling some
controversies. In J. Littlemore & J. Taylor (Eds.). Bloomsbury
Companion to Cognitive
Linguistics (pp. 143–166). Bloomsbury.
Ruiz de Mendoza, F. J. (2017). Cognitive
modeling and irony. In H. Colson & A. Athanasiadou (Eds.). Irony
in language use and
communication (pp. 179–200). John Benjamins.
Ruiz de Mendoza, F. J. (2020). Understanding
figures of speech: Dependency relations and organizational patterns. Language
&
Communication, 71, 16–38.
Ruiz de Mendoza, F. J., & Lozano-Palacio, I. (2019a). Unraveling
irony: From linguistics to literary criticism and back. Cognitive
Semantics 5, 147–173.
Ruiz de Mendoza, F. J., & Lozano-Palacio, I. (2019b). A
cognitive-linguistic approach to complexity in irony: Dissecting the ironic
echo. Metaphor
Symbol 34 (2), 127–138.
Sperber, D. (1984). VI:
Pretense or echoic mention? Journal of Experimental Psychology:
General, 113(1), 130–136.
Sperber, D., & Wilson, D. (1981). Irony
and the use-mention distinction. In P. Cole (Ed.), Radical
pragmatics (pp. 295–318). Academic Press.
Sulis, E., Hernandez Faras, D. I., Rosso, P., Patti, V., & Ruffo, G. (2016). Figurative
messages and affect in Twitter: Differences between #irony, #sarcasm and
#not. Knowledge-Based
Systems, 108, 132–143.
Tobin, V., & Israel, M. (2012). Irony
as a viewpoint phenomenon. In B. Dancygier & E. Sweetser (Eds.), Viewpoint
in
language (pp. 24–46). Cambridge University Press.
Van Hee, C., Lefever, E., & Hoste, V. (2018). Semeval-2018
task 3: Irony detection in English tweets. Proceedings of The 12th
International Workshop on Semantic
Evaluation (pp. 39–50).
Wallace, B. C. (2015). Computational
irony: A survey and new perspectives. Artificial Intelligence
Review, 43(4), 467–483.
Walton, K. (2017). Meiosis,
hyperbole, irony. Philos.
Stud. 174(1), 105–120.
Wang, P. Y. A. (2013). #irony
or #sarcasm, a quantitative and qualitative study based on
Twitter. Proceedings of the 27th Pacific Asia Conference on
Language, Information, and Computation (PACLIC
27) (pp. 349–356). Dept.
of English, National Chengchi University.
Wilson, D. (2006). The
pragmatics of VI: Echo or pretence? Lingua, 116, 1722–1743.
Wilson, D. (2013). Irony
comprehension: A developmental perspective. Journal of
Pragmatics, 59, 40–46.
Wilson, D., & Sperber, D. (2012). Explaining
irony. In D. Wilson & D. Sperber (Eds.). Meaning
and
relevance (pp. 123–145). Cambridge University Press.
Young, T., Hazarika, D., Poria, S., & Cambria, E. (2018). Recent
trends in deep learning based natural language processing. IEEE Computational
Intelligence
magazine, 13(3), 55–75.