prikaz prve stranice dokumenta Modeli za predviđanje religijske pripadnosti autora teksta
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master's thesis
Modeli za predviđanje religijske pripadnosti autora teksta
2018. urn:nbn:hr:168:550947
Brassard, Ana
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Brassard, A. (2018). Modeli za predviđanje religijske pripadnosti autora teksta (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:550947

Brassard, Ana. "Modeli za predviđanje religijske pripadnosti autora teksta." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:550947

Brassard, Ana. "Modeli za predviđanje religijske pripadnosti autora teksta." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:550947

Brassard, A. (2018). 'Modeli za predviđanje religijske pripadnosti autora teksta', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 01 April 2025, https://urn.nsk.hr/urn:nbn:hr:168:550947

Brassard A. Modeli za predviđanje religijske pripadnosti autora teksta [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2025 April 01] Available at: https://urn.nsk.hr/urn:nbn:hr:168:550947

A. Brassard, "Modeli za predviđanje religijske pripadnosti autora teksta", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:550947

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Metadata
TitleModeli za predviđanje religijske pripadnosti autora teksta
Title (english)Text-based Religious Affiliation Prediction
AuthorAna Brassard
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberDomagoj Jakobović (član povjerenstva)
Committee memberMarko Čupić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-09-26, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu odrađen je zadatak klasificiranja korisnika mrežnog foruma “Reddit” koji sudjeluju u debatama religijske tematike u podforumu “/r/DebateReligion” po njihovom religijskom opredjeljenju. Podaci su prvo obrađeni da bi se kreirao popis religija koje će se klasificirati, što je rezultiralo ukupno dvadeset i jednom klasom. Klase su iznimno neuravnotežene po broju korisnika u njima, te uz to ih ima velik broj. Izgrađen je sustav koji predviđa metodom glasovanja temeljnih klasifikatora... More koristeći LIWC značajke: skup 210 strojeva potpornih vektora, po jedan za svaki par klasa. Less
Abstract (english)
This work attempts to classify the religious affiliation of users of the social website “Reddit” that participate in religious debate in the “/r/DebateReligion” community. The data is first processed in order to create a list of religions to classify, which resulted in a twenty-one class list. The classes are extremely unbalanced and numerous. A base estimator voting system using LIWC features was built: a set of 210 support vector machines, one per pair of classes.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:550947
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
Terms of useLicence In copyright icon
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Created on2019-03-13 19:17:26
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