prikaz prve stranice dokumenta Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama
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undergraduate thesis
Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:289130
Šmigovec, Dunja
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Šmigovec, D. (2021). Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:289130

Šmigovec, Dunja. "Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:289130

Šmigovec, Dunja. "Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:289130

Šmigovec, D. (2021). 'Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 16 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:289130

Šmigovec D. Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 July 16] Available at: https://urn.nsk.hr/urn:nbn:hr:168:289130

D. Šmigovec, "Modeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:289130

Metadata
TitleModeli obrade prirodnog jezika za detekciju sarkazma na društvenim mrežama
Title (english)Natural Language Processing Models for Sarcasm Detection on Social Media
AuthorDunja Šmigovec
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberIvan Crnomarković (član povjerenstva)
Committee memberZoran Medić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Obrada prirodnog jezika je grana umjetne inteligencije, koja pomaže računalima u određivanju sentimenta te značajnih dijelova jezika. Detekcija sarkazma specifičan je slučaj analize sentimenta i predstavlja izazovan zadatak u obradi prirodnog jezika. Budući da sarkazam koristi suprotni sentiment, teško ga je razumjeti, ne samo za strojeve, već i za ljude. U ovom radu ispitane su metode strojnog i dubokog učenja za klasifikaciju sarkazma u objavama na društvenim mrežama. Naša dva glavna pristupa uključuju BiLSTM modele, koji uzimaju u obzir odgovor i različite duljine konteksta. Zaključujemo da previše konteksta smanjuje točnost modela. Primjećujemo da pristupi dubokog učenja daju bolje rezultate od pristupa strojnog učenja.
Abstract (english)
Natural language processing is a branch of artificial intelligence, that helps computers to measure sentiment and determine which parts of language are significant. Sarcasm detection is a specific case of sentiment analysis and presents a challenging task in natural language processing. Because sarcasm uses the opposite sentiment, it is hard to understand, not only for machines but also for humans. In this thesis, we test machine and deep learning methods for sarcasm classification in social media posts. Our two main approaches include BiLSTM models that take the response and various lengths of context into consideration. We conclude that too much context reduces the accuracy of the model. We observe that deep learning approaches yield better results than machine learning.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:289130
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 on2023-01-14 21:47:54