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undergraduate thesis
Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:220942
Pavlić, Josip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Pavlić, J. (2024). Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:220942

Pavlić, Josip. "Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:220942

Pavlić, Josip. "Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:220942

Pavlić, J. (2024). 'Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 29 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:220942

Pavlić J. Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 November 29] Available at: https://urn.nsk.hr/urn:nbn:hr:168:220942

J. Pavlić, "Primjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:220942

Metadata
TitlePrimjena i vrednovanje metoda za detekciju sarkazma u engleskome jeziku
Title (english)Application and evaluation of methods for detecting sarcasm in the English language
AuthorJosip Pavlić
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberDavid Dukić (član povjerenstva)
Committee memberAna Barić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj završni rad bavi se primjenom i vrednovanjem metoda za detekciju sarkazma u engleskom jeziku. Cilj je bio ispitati učinkovitost različitih modela strojnog učenja, uključujući stroj potpornih vektora (SVM), BERT i višezadaćno učenje, na tri podzadatka: identifikacija sarkazma, određivanje podkategorija sarkastičnih tekstova i prepoznavanje sarkazma u rečenicama i njihovim nesarkastičnim inačicama. Rezultati pokazuju da modeli BERT daju bolje rezultate od SVM-a, dok višezadaćno učenje nije pokazalo poboljšanja zbog velike razlike u prirodi podzadataka i ograničenosti skupa podataka.
Abstract (english)
This thesis explores the application and evaluation of methods for detecting sarcasm in the English language. The aim was to examine the effectiveness of various machine learning models, including Support Vector Machines (SVM), BERT, and multitask learning, on three subtasks: identifying sarcasm, determining subcategories of sarcastic texts, and recognizing sarcasm in sentences and their non-sarcastic paraphrases. The results show that BERT models perform better than SVM, while multitask learning did not show improvements due to the significant difference in the nature of the subtasks and the limitations of the dataset.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:220942
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2024-10-12 21:47:42