prikaz prve stranice dokumenta Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku
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master's thesis
Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:898215
Gracin, Franko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Gracin, F. (2022). Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:898215

Gracin, Franko. "Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:898215

Gracin, Franko. "Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:898215

Gracin, F. (2022). 'Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 16 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:898215

Gracin F. Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 June 16] Available at: https://urn.nsk.hr/urn:nbn:hr:168:898215

F. Gracin, "Uporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:898215

Metadata
TitleUporaba transformer modela u analizi sentimenata tekstualnih sekvenci na hrvatskom jeziku
Title (english)Use of transformer models in the analysis of sentiments of textual sequences in the Croatian language
AuthorFranko Gracin
MentorMarko Horvat (mentor)
Committee memberMarko Horvat (predsjednik povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
Committee memberMarina Bagić Babac (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-09-19, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Zbog trenutne aktualnosti teme COVID-19 pandemije u ovom radu koristi se predtrenirani trojezični CrosloEngual model za analizu promjene sentiment na hrvatskom podatkovnom podskup prikupljenom prije početka COVID-19 pandemije i te podskupu kreiran neposredno nakon početka pandemije. Pošto navedeni skup podataka je neoznačen prvotno se model fino podešava na sličnom skupu slovenskih i hrvatskih novinskih članaka te se zatim klasificira i analizira sentiment prikupljenog COVID-19 skupa podataka. Završna analiza upućuje na moguća ne podudaranje skupova podataka za treniranje i COVID-19 skupa podataka zbog velikih ne uravnoteženosti između distribucija klasa predviđenog sentimenta na COVID-19 skupu podataka.
Abstract (english)
Due to the current popularity of the COVID-19 pandemic, this paper uses a pre-trained trilingual CrosloEngual model to analyze sentiment change in the Croatian data subset collected before the COVID-19 pandemic and the subset created immediately after the pandemic. Since the mentioned dataset is unmarked, the model is initially fine-tuned on a similar set of Slovenian and Croatian news articles, and then the sentiment of the collected COVID-19 data set is classified and analyzed. The final analysis suggests a possible mismatch of the training datasets and the COVID-19 dataset due to large imbalances between class distributions on predicted sentiment of the COVID-19 dataset.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:898215
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2023-01-14 08:50:29