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undergraduate thesis
Primjena strojnog učenja za tematsku analizu sentimenta
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. urn:nbn:hr:168:348565
Mikulić, Stipan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Mikulić, S. (2016). Primjena strojnog učenja za tematsku analizu sentimenta (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:348565

Mikulić, Stipan. "Primjena strojnog učenja za tematsku analizu sentimenta." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:348565

Mikulić, Stipan. "Primjena strojnog učenja za tematsku analizu sentimenta." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:348565

Mikulić, S. (2016). 'Primjena strojnog učenja za tematsku analizu sentimenta', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:348565

Mikulić S. Primjena strojnog učenja za tematsku analizu sentimenta [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2016 [cited 2024 November 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:348565

S. Mikulić, "Primjena strojnog učenja za tematsku analizu sentimenta", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:168:348565

Metadata
TitlePrimjena strojnog učenja za tematsku analizu sentimenta
Title (english)Application of Machine Learning for Topic-Based Sentiment Analysis
AuthorStipan Mikulić
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberDomagoj Alagić (član povjerenstva)
Committee memberMladen Karan (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2016-07-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Uslijed ogromnog povećanja korisnički generiranog sadržaja na društvenih mrežama, detekcija tema i analiza sentimenta nameću se kao nezaobilazni alati za analizu javnog mijenja. U radu su proučeni postupci za detekciju tema u tekstnih dokumenata te anal- izu sentimenta prema detektiranim temama. Naglasak je stavljen na postupke temel- jene na modelima strojnog učenja. Detekcijom tema nastoje se prepoznati teme o kojima se priča na društvenim mrežama te analizom sentimenta se odred̄uje da li je stav o tim temama pozitivan, negativan ili neutralan. Rad se sastoji od cijelog procesa prikupljanja i preprocesiranja podataka. Nakon toga slijedi izgradnja modela detekcije tema i analize sentimenta te evaluacija modela. Dodatno, za analizu sentimenta je bilo potrebno označiti podatke za treniranje modela.
Abstract (english)
Due to the huge increase in user-generated content on social networks, topic detec- tion and sentiment analysis imposed as indispensable tools for the analysis of public opinion. The thesis examines the procedures for the topic detection in text documents and an sentiment analysis towards the detected topics. Special focus is placed on a procedures based on machine learning. Topic detection attempts to identify the topics on which the story on social networks and sentiment analysis to determine whether the position on these issues is positive, negative or neutral. The work consists of the en- tire process of collecting and preprocessing data. This is followed by the construction of topic detection and sentiment analysis models and evaluation of those models. In addition, sentiment analysis required data annotation for training the model.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:348565
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 on2018-02-06 10:43:46