Otkrivanje govora mržnje na društvenim mrežama pomoću strojnog učenja

undergraduate thesis

• Title (english): Hate Speech Detection on Social Networks Using Machine Learning
• Author: Fabijan Čorak
• Mentor: Jan Šnajder (mentor)
• Committee member: Jan Šnajder (predsjednik povjerenstva)
• Committee member: Mladen Karan (član povjerenstva)
• Committee member: Domagoj Alagić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2018-07-13, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U jeku razvoja Interneta podstrek dobivaju i nepoželjeni oblici komunikacije, izmedu
ostaloga govor mržnje. Automatizaciji njegova otkrivanja pristupili su brojni znanstvenici s područja obrade prirodnog jezika i strojnog učenja. U obzir uzimaju mnogobrojne značajke i primjenjuju različite modele s uglavnom solidnom, no ne i idealnom ucinkovitošću. Ovaj rad eksperimentalno pokazuje da model treniran na jednom skupu podataka teško daje dobre rezultate na ulazu iz drugog, nesrodnog skupa... More podataka. Bolji rezultati ostvarivi su uz prilagodbu okružju treniranjem na prikladnim podatcima. Less

Abstract (english)

The development of Internet stimulates, among other things, undesirable forms of communication, including hate speech. The automation of its detection has been attempted by numerous scientists from the field of natural language processing and machine learning. They have tried extracting many features and applying different models with mostly , but not ideal efficiency. This thesis experimentally shows that models trained on one dataset often fail when utilized on other, unrelated... More datasets. Better results can be achieved by adaptation through training on appropriate data. Less

• Keywords: govor mržnje; strojno učenje; ML; obrada prirodnog jezika; NLP; društvene mreže; Twitter
• Keywords (english): hate speech; machine learning; ML; natural language processing; NLP; social networks; Twitter
• Language: croatian
• URN:NBN: urn:nbn:hr:168:906344
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-03-13 19:45:28