prikaz prve stranice dokumenta Analiza sentimenta u glazbenim tekstovima
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undergraduate thesis
Analiza sentimenta u glazbenim tekstovima
2020. urn:nbn:hr:168:720388
Marijić, Antonijo
University of Zagreb
Faculty of Electrical Engineering and Computing

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Marijić, A. (2020). Analiza sentimenta u glazbenim tekstovima (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:720388

Marijić, Antonijo. "Analiza sentimenta u glazbenim tekstovima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:720388

Marijić, Antonijo. "Analiza sentimenta u glazbenim tekstovima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:720388

Marijić, A. (2020). 'Analiza sentimenta u glazbenim tekstovima', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:720388

Marijić A. Analiza sentimenta u glazbenim tekstovima [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 April 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:720388

A. Marijić, "Analiza sentimenta u glazbenim tekstovima", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:720388

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Metadata
TitleAnaliza sentimenta u glazbenim tekstovima
Title (english)Music Lyrics Mining and Sentiment Analysis
AuthorAntonijo Marijić
MentorMarina Bagić Babac (mentor)
Committee memberMarina Bagić Babac (predsjednik povjerenstva)
Committee memberNikica Hlupić (član povjerenstva)
Committee memberKrešimir Fertalj (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Analiza sentimenta stihova važan je dio glazbenih sustava za preporučivanje jer se koristi za klasifikaciju pjesama. No, pronalaženje točnih klasifikatora je izuzetno zahtjevno zbog nedostatka sveobuhvatnih skupova podataka. Na temelju velikog skupa tekstova pjesama, ovaj završni rad istražuje postupke automatske obrade skupa podataka i analize sentimenta na temelju afektivnih leksikona. Rezultati naznačuju kakve se afektivne dimenzije mogu prepoznati te kako se mogu interpretirati.
Abstract (english)
Sentiment analysis of lyrics is an important part of music recommendation systems as it is used for classification od songs. However, finding accurate classifiers remains a challenging task due to lack of comprehensive lyrics datasets. Based on a large dataset of lyrics, this thesis explores the process of automatic pre-processing of datasets and sentiment analysis based on use of affective lexicons. The results indicate what kind of affective dimensions can be recognized, and how they can be interpreted.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:720388
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 09:25:53