prikaz prve stranice dokumenta Analiza sentimenta novinskih članaka
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master's thesis
Analiza sentimenta novinskih članaka
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:441229
Barić, Ana
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Barić, A. (2022). Analiza sentimenta novinskih članaka (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:441229

Barić, Ana. "Analiza sentimenta novinskih članaka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:441229

Barić, Ana. "Analiza sentimenta novinskih članaka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:441229

Barić, A. (2022). 'Analiza sentimenta novinskih članaka', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:441229

Barić A. Analiza sentimenta novinskih članaka [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 July 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:441229

A. Barić, "Analiza sentimenta novinskih članaka", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:441229

Metadata
TitleAnaliza sentimenta novinskih članaka
Title (english)News Sentiment Analysis
AuthorAna Barić
MentorTomislav Burić (mentor)
Committee memberTomislav Burić (predsjednik povjerenstva)
Committee memberMervan Pašić (član povjerenstva)
Committee memberLenka Mihoković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovog rada bio je razvoj modela za strojnu evaluaciju sentimenta u novinskim člancima. Tip sentimenta koji se izučavao bio je ciljani sentiment, odnosno sentiment prema ciljnom entitetu na razini rečenice. U sklopu razvoja modela za analizu sentimenta u ovom radu označen skup od 1636 podataka koji su bili korišteni za treniranje i evaluaciju modela. Za razvoj modela koristili su se pristupi iz domene dubokog učenja. Implementacija ovog rada obuhvaća razvoj cjevovoda za preprocesiranje podataka te implementaciju i evaluaciju unaprijednih i povratnih dubokih modela te podešavanje BERTić modela.
Abstract (english)
This paper aimed to develop a model for the machine evaluation of sentiment in newspaper articles. The type of sentiment studied was targeted sentiment, that is, sentiment toward the target entity at the sentence level. As part of developing the sentiment analysis model, a set of 1636 manually annotated data points was used to train and evaluate the model. Deep learning approaches were used to develop the model. The implementation of this paper includes the development of pipelines for data preprocessing and the implementation and evaluation of feed-forward and recurrent deep models and BERTić fine-tuning.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:441229
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
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Created on2023-01-13 14:28:20