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master's thesis
Sustav za analizu te analiza komentara novinskih članaka
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:060231
Bakula, Silvana
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bakula, S. (2022). Sustav za analizu te analiza komentara novinskih članaka (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:060231

Bakula, Silvana. "Sustav za analizu te analiza komentara novinskih članaka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:060231

Bakula, Silvana. "Sustav za analizu te analiza komentara novinskih članaka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:060231

Bakula, S. (2022). 'Sustav za analizu te analiza komentara novinskih članaka', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:060231

Bakula S. Sustav za analizu te analiza komentara novinskih članaka [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:060231

S. Bakula, "Sustav za analizu te analiza komentara 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:168:060231

Metadata
TitleSustav za analizu te analiza komentara novinskih članaka
Title (english)System for analysis, and analysis of news articles comments
AuthorSilvana Bakula
MentorStjepan Groš (mentor)
Committee memberStjepan Groš (predsjednik povjerenstva)
Committee memberJan Šnajder (član povjerenstva)
Committee memberDejan Škvorc (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Internet je omogućio nastanak mnogih portala i društvenih mreža preko kojih se prenose vijesti iz svih domena. Određene teme pobuđuju visok interes javnosti i pokreću lavinu komentara. Porast računalne snage i memorijskih kapaciteta je omogućio pohranjivanje i analiziranje tih komentara. Cilj ovog rada je pokušati odgovoriti na pitanje je li moguće prepoznati i kvantificirati stil pisanja koji jedinstveno pripada svakom čovjeku i na taj način povezati komentar sa stvarnim autorom. Korištene su metode iz domene stilometrije u kombinaciji s algoritmima nadziranog strojnog učenja. Potrebno je pronaći način kako poboljšati robusnost modela da može rukovati s kratkim komentarima jer prema predloženoj shemi mali skup kratkih komentara nije dovoljan za prepoznavanje univerzalnog jezičnog obrasca.
Abstract (english)
The flow of news is growing every day on social media. Some topics arouse high interest in the public and trigger an avalanche of comments. Processors and memory capacity improvements have made it possible to save and process these comments. The main goal of this thesis is to answer if it is possible to extract and quantify linguistic features by which it is possible to distinguish different authors. Authorship attribution is implemented using stylometric techniques and supervised machine learning algorithms. It is necessary to improve the robustness of the model to be able to handle short comments because according to the proposed scheme a small set of short comments is not enough to recognise a universal writing style.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:060231
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 on2023-01-14 20:02:48