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undergraduate thesis
Prepoznavanje internetskog nasilja pomoću strojnog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:231166
Zaninović, Ana
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Zaninović, A. (2024). Prepoznavanje internetskog nasilja pomoću strojnog učenja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:231166

Zaninović, Ana. "Prepoznavanje internetskog nasilja pomoću strojnog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:231166

Zaninović, Ana. "Prepoznavanje internetskog nasilja pomoću strojnog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:231166

Zaninović, A. (2024). 'Prepoznavanje internetskog nasilja pomoću strojnog učenja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 01 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:231166

Zaninović A. Prepoznavanje internetskog nasilja pomoću strojnog učenja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2025 January 01] Available at: https://urn.nsk.hr/urn:nbn:hr:168:231166

A. Zaninović, "Prepoznavanje internetskog nasilja pomoću strojnog učenja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:231166

Metadata
TitlePrepoznavanje internetskog nasilja pomoću strojnog učenja
Title (english)Predicting Cyberbullying using Machine Learning
AuthorAna Zaninović
MentorMarina Bagić Babac (mentor)
Committee memberMarina Bagić Babac (predsjednik povjerenstva)
Committee memberMelita Fertalj (član povjerenstva)
Committee memberKristijan Poje (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-06-20, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ova teza ima za cilj analizirati podatke s društvenih mreža i prepoznati sadržaj koji uključuje vršnjačko nasilje. Prvo je nad korištenim datasetom provedena analiza emocija uporabom skupova podataka NRC Emotion Intensity Lexicona (NRC EIL) za otkrivanje distribucije emocija. Korišteni skupovi podataka sastoje se od uzoraka teksta prikupljenih s različitih društvenih mreža, zajedno s odgovarajućim oznakama koje ukazuju na prisutnost različitih čimbenika koji uključuju vršnjačko nasilje, agresiju, napad, toksičnost te nasilje na temelju dobi, spola, religije, etničke pripadnosti i drugih čimbenika. Tekstovi su obrađeni uz pomoć tehnika kao što su tokenizacija, stemanje i uklanjanje zaustavnih riječi kako bi se očistili tekstualni podaci. Zatim su korišteni algoritmi strojnog učenja kao što su Naive Bayes, Multinomial NM, Bernoulli NB, Logistic Regression, SGDC, SVC, Linear SVC i NuSVC za klasifikaciju teksta.
Abstract (english)
This thesis aimed to analyze social media data and recognize whether or not it contains bullying. First, emotion analysis of used datasets was made using NRC Emotion Intensity Lexicon (NRC EIL) for detecting emotion distribution. The used datasets consisted of text samples collected from various social media platforms, and corresponding labels which indicated present of different factors including bullying, aggression, attack, toxicity, and bullying on the basis of age, gender, religion, ethnicity and other factors. Preprocessing techniques like tokenization, stemming, and stop-word removal were applied to clean the text data. Then, machine learning algorithms like Naive Bayes, Multinomial NM, Bernoulli NB, Logistic Regression, SGDC, SVC, Linear SVC and NuSVC were utilized for text classification.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:231166
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 on2024-10-12 22:31:36