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undergraduate thesis
Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:720918
Pavlović, Luka
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Pavlović, L. (2021). Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:720918

Pavlović, Luka. "Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:720918

Pavlović, Luka. "Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:720918

Pavlović, L. (2021). 'Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:720918

Pavlović L. Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 November 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:720918

L. Pavlović, "Otkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:720918

Metadata
TitleOtkrivanje prisutnosti stresa u objavama na Redditu pomoću obrade prirodnog jezika
Title (english)Detecting Presence of Stress in Reddit Posts Using Natural Language Processing
AuthorLuka Pavlović
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberIvan Crnomarković (član povjerenstva)
Committee memberZoran Medić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovog rada bio je razvoj modela strojnog učenja koji će uspješno otkrivati prisutnost stresa u objavama na Redditu. Skup podataka korišten u ovom radu stvorili su istraživači sa Sveučilišta Columbia. Skup podataka stvoren je web-scrapingom društvene mreže Reddit. Podaci su podijeljeni po domenama koje sadrže jedan subreddit ili više njih. Iako skup podataka sadrži veći broj značajki, samo tri su korištene u ovom radu, a to su: subreddit, tekst objave i oznaka koja označava prisutnost stresa. U pokušaju stvaranja modela koji će imati zadovoljavajuće performanse izgrađena su četiri modela. Kao osnovni modeli stvoreni su: klasifikator većinske klase te stroj potpornih vektora (engl. Support Vector Machine, SVM), koji je koristio Term Frequency-Inverse Document Frequency vektore. Također, stvorene su dvije verzije modela dubokog učenja: Long Short-Term Memory (LSTM) s globalnim vektorima za reprezentaciju riječi (engl. Global Vectors for Word Representation, GloVe) i LSTM s vektorizatorom FastText. Model SVM i model LSTM s GloVe optimizirani su na najbolje hiperparametre te su evaluirani na skupu za testiranje. Unatoč visokim očekivanjima od modela dubokog učenja, najbolje rezultate dao je model SVM.
Abstract (english)
The aim of this thesis was to develop a machine learning model that will successfully detect the presence of stress in Reddit posts. The dataset used in this thesis was created by researchers from Columbia University. The dataset was created by scraping of social network Reddit. Data is divided into domains that contain one or more subreddits. Although the dataset contains a number of features, only three were used for purposes of this thesis, namely: subreddit, users’ post text, and a label indicating the presence of stress. Four models were built in an attempt to create a model that would have satisfactory performance. As baseline models, the following have been created: majority class baseline and Support Vector Machine (SVM) which uses TF-IDF vectors. Also, two versions of the deep learning model were created: Long Short-Term Memory (LSTM) with GloVe vectors and LSTM with FastText vectorizer. SVM model and LSTM with GloVe were optimized for the best hyperparameters and evaluated on the test set. Despite high expectations from the deep learning model, the best results were obtained using the SVM model.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:720918
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
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Created on2023-01-14 21:23:40