Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/36264
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dc.contributor.authorCakebread-Andrews, Oliveren_UK
dc.contributor.authorHa, Le Anen_UK
dc.contributor.authorFrommholz, Ingoen_UK
dc.contributor.authorCan, Burcuen_UK
dc.date.accessioned2024-10-03T00:13:21Z-
dc.date.available2024-10-03T00:13:21Z-
dc.date.issued2024en_UK
dc.identifier.urihttp://hdl.handle.net/1893/36264-
dc.description.abstractThis paper summarises the differences and similarities found between humans and three natural language processing models when attempting to identify whether English online comments are sarcastic or not. Three models were used to analyse 300 comments from the FigLang 2020 Reddit Dataset, with and without context. The same 300 comments were also given to 39 non-native speakers of English and the results were compared. The aim was to find whether there were any results that could be applied to English as a Foreign Language (EFL) teaching. The results showed that there were similarities between the models and non-native speakers, in particular the logistic regression model. They also highlighted weaknesses with both non-native speakers and the models in detecting sarcasm when the comments included political topics or were phrased as questions. This has potential implications for how the EFL teaching industry could implement the results of error analysis of NLP models in teaching practices.en_UK
dc.language.isoenen_UK
dc.publisherELRA Language Resource Associationen_UK
dc.relationCakebread-Andrews O, Ha LA, Frommholz I & Can B (2024) Error Analysis of NLP Models and Non-Native Speakers of English Identifying Sarcasm in Reddit Comments. In: LREC-COLING 2024, Torino, 20.05.2024-25.07.2024. ELRA Language Resource Association, pp. 6247-6256. https://aclanthology.org/2024.lrec-main.552.pdfen_UK
dc.rights© 2024 ELRA Language Resource Association: CC BY-NC 4.0en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectSentiment Analysisen_UK
dc.subjectSarcasm Detectionen_UK
dc.subjectTEFLen_UK
dc.titleError Analysis of NLP Models and Non-Native Speakers of English Identifying Sarcasm in Reddit Commentsen_UK
dc.typeConference Paperen_UK
dc.citation.spage6247en_UK
dc.citation.epage6256en_UK
dc.citation.publicationstatusPublisheden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.identifier.urlhttps://aclanthology.org/2024.lrec-main.552.pdfen_UK
dc.author.emailburcu.can@stir.ac.uken_UK
dc.citation.conferencedates2024-05-20 - 2024-07-25en_UK
dc.citation.conferencelocationTorinoen_UK
dc.citation.conferencenameLREC-COLING 2024en_UK
dc.citation.date01/05/2024en_UK
dc.contributor.affiliationUniversity of Wolverhamptonen_UK
dc.contributor.affiliationUniversity of Wolverhamptonen_UK
dc.contributor.affiliationUniversity of Wolverhamptonen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.wtid2033473en_UK
dc.date.accepted2024-03-01en_UK
dcterms.dateAccepted2024-03-01en_UK
dc.date.filedepositdate2024-07-30en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeConference Paper/Proceeding/Abstracten_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorCakebread-Andrews, Oliver|en_UK
local.rioxx.authorHa, Le An|en_UK
local.rioxx.authorFrommholz, Ingo|en_UK
local.rioxx.authorCan, Burcu|en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2024-09-26en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by-nc-nd/4.0/|2024-09-26|en_UK
local.rioxx.filename2024.lrec-main.552.pdfen_UK
local.rioxx.filecount1en_UK
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