Does anyone see the irony here? Analysis of perspective-aware model predictions in irony detection
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A6HVA3Z27" target="_blank" >RIV/00216208:11320/23:6HVA3Z27 - isvavai.cz</a>
Výsledek na webu
<a href="https://iris.unito.it/handle/2318/1945382" target="_blank" >https://iris.unito.it/handle/2318/1945382</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Does anyone see the irony here? Analysis of perspective-aware model predictions in irony detection
Popis výsledku v původním jazyce
"In the framework of perspectivism, analyzing how people perceive pragmatic phenomena, like irony, is relevant for deeply understanding the different points of view, and for creating more robust perspective-aware models. This paper presents a linguistic analysis of irony perception in 11 perspectivist models. Each model is trained on annotations by crowd-sourcing workers different in gender, age, and nationalities. Due to the sparsity of the dataset, we examine the texts classified as ironic and not-ironic by these perspectivist models, and identify linguistic patterns that all perspectives associate with irony. To our knowledge, we are the first to also provide evidence for the different linguistic patterns perceived as ironic by a specific perspective. For example, models trained on data annotated by American and Australian annotators are more inclined to classify a text as ironic when it includes a negative sentiment, while models trained on data annotated by the youngest annotators are particularly influenced by words related to immoral behaviors. Warning: This paper could contain content that is offensive or upsetting for the reader."
Název v anglickém jazyce
Does anyone see the irony here? Analysis of perspective-aware model predictions in irony detection
Popis výsledku anglicky
"In the framework of perspectivism, analyzing how people perceive pragmatic phenomena, like irony, is relevant for deeply understanding the different points of view, and for creating more robust perspective-aware models. This paper presents a linguistic analysis of irony perception in 11 perspectivist models. Each model is trained on annotations by crowd-sourcing workers different in gender, age, and nationalities. Due to the sparsity of the dataset, we examine the texts classified as ironic and not-ironic by these perspectivist models, and identify linguistic patterns that all perspectives associate with irony. To our knowledge, we are the first to also provide evidence for the different linguistic patterns perceived as ironic by a specific perspective. For example, models trained on data annotated by American and Australian annotators are more inclined to classify a text as ironic when it includes a negative sentiment, while models trained on data annotated by the youngest annotators are particularly influenced by words related to immoral behaviors. Warning: This paper could contain content that is offensive or upsetting for the reader."
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
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Návaznosti
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Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
"CEUR WORKSHOP PROCEEDINGS"
ISBN
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ISSN
1613-0073
e-ISSN
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Počet stran výsledku
11
Strana od-do
1-11
Název nakladatele
CEUR-WS
Místo vydání
Kraków, Poland
Místo konání akce
Kraków, Poland
Datum konání akce
1. 1. 2023
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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