@inproceedings{kuhn-mitrovic-2024-elephant,
title = "The Elephant in the Room: Ten Challenges of Computational Detection of Rhetorical Figures",
author = {K{\"u}hn, Ramona and
Mitrovi{\'c}, Jelena},
editor = "Ghosh, Debanjan and
Muresan, Smaranda and
Feldman, Anna and
Chakrabarty, Tuhin and
Liu, Emmy",
booktitle = "Proceedings of the 4th Workshop on Figurative Language Processing (FigLang 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.figlang-1.6",
doi = "10.18653/v1/2024.figlang-1.6",
pages = "45--52",
abstract = "Computational detection of rhetorical figures focuses mostly on figures such as metaphor, irony, or analogy. However, there exist many more figures that are neither less important nor less prevalent. We wanted to pinpoint the reasons why researchers often avoid other figures and to shed light on the challenges they struggle with when investigating those figures. In this comprehensive survey, we analyzed over 40 papers dealing with the computational detection of rhetorical figures other than metaphor, simile, sarcasm, and irony. We encountered recurrent challenges from which we compiled a ten point list. Furthermore, we suggest solutions for each challenge to encourage researchers to investigate a greater variety of rhetorical figures.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kuhn-mitrovic-2024-elephant">
<titleInfo>
<title>The Elephant in the Room: Ten Challenges of Computational Detection of Rhetorical Figures</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ramona</namePart>
<namePart type="family">Kühn</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jelena</namePart>
<namePart type="family">Mitrović</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-06</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 4th Workshop on Figurative Language Processing (FigLang 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Debanjan</namePart>
<namePart type="family">Ghosh</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Smaranda</namePart>
<namePart type="family">Muresan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anna</namePart>
<namePart type="family">Feldman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tuhin</namePart>
<namePart type="family">Chakrabarty</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Emmy</namePart>
<namePart type="family">Liu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Mexico City, Mexico (Hybrid)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Computational detection of rhetorical figures focuses mostly on figures such as metaphor, irony, or analogy. However, there exist many more figures that are neither less important nor less prevalent. We wanted to pinpoint the reasons why researchers often avoid other figures and to shed light on the challenges they struggle with when investigating those figures. In this comprehensive survey, we analyzed over 40 papers dealing with the computational detection of rhetorical figures other than metaphor, simile, sarcasm, and irony. We encountered recurrent challenges from which we compiled a ten point list. Furthermore, we suggest solutions for each challenge to encourage researchers to investigate a greater variety of rhetorical figures.</abstract>
<identifier type="citekey">kuhn-mitrovic-2024-elephant</identifier>
<identifier type="doi">10.18653/v1/2024.figlang-1.6</identifier>
<location>
<url>https://aclanthology.org/2024.figlang-1.6</url>
</location>
<part>
<date>2024-06</date>
<extent unit="page">
<start>45</start>
<end>52</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T The Elephant in the Room: Ten Challenges of Computational Detection of Rhetorical Figures
%A Kühn, Ramona
%A Mitrović, Jelena
%Y Ghosh, Debanjan
%Y Muresan, Smaranda
%Y Feldman, Anna
%Y Chakrabarty, Tuhin
%Y Liu, Emmy
%S Proceedings of the 4th Workshop on Figurative Language Processing (FigLang 2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico (Hybrid)
%F kuhn-mitrovic-2024-elephant
%X Computational detection of rhetorical figures focuses mostly on figures such as metaphor, irony, or analogy. However, there exist many more figures that are neither less important nor less prevalent. We wanted to pinpoint the reasons why researchers often avoid other figures and to shed light on the challenges they struggle with when investigating those figures. In this comprehensive survey, we analyzed over 40 papers dealing with the computational detection of rhetorical figures other than metaphor, simile, sarcasm, and irony. We encountered recurrent challenges from which we compiled a ten point list. Furthermore, we suggest solutions for each challenge to encourage researchers to investigate a greater variety of rhetorical figures.
%R 10.18653/v1/2024.figlang-1.6
%U https://aclanthology.org/2024.figlang-1.6
%U https://doi.org/10.18653/v1/2024.figlang-1.6
%P 45-52
Markdown (Informal)
[The Elephant in the Room: Ten Challenges of Computational Detection of Rhetorical Figures](https://aclanthology.org/2024.figlang-1.6) (Kühn & Mitrović, Fig-Lang-WS 2024)
ACL