Aspect-Oriented Sentiment Analysis from User Reviews of Computer Games

Táto bakalárska práca sa zaoberá problematikou aspektovo-orientovanej analýzy sentimentu a implementáciou systému určeného k analýze používateľských recenzií videohier. Pri tvorbe systému nadväzuje na súčasne riešenia a zameriava sa na aplikovanie generatívnych jazykových modelov pre úlohu extrakcie štvoríc (aspekt, kategória, názor, sentiment). Vytvorený systém dokáže automatizovať proces získavania a analýzy recenzií. Pomocou webovej aplikácie poskytuje intuitívne používateľské rozhranie pre vyhľadávanie, filtrovanie a vizualizáciu výsledkov analýzy. Pre účely práce boli taktiež vytvorené dve dátové sady prevažne českých recenzií videohier.This bachelor's thesis delves into aspect-based sentiment analysis (ABSA) and the creation of a system tailored for examining video game user reviews. By building on established solutions, the system emphasizes the use of generative language models for extracting Aspect-Category-Opinion-Sentiment (ACOS) quadruples. The devised system streamlines the collection and evaluation of reviews, providing an intuitive user interface that enables effortless searching, filtering, and visualization of analytical outcomes via a web application. Furthermore, two datasets predominantly consisting of Czech video game reviews have been assembled.

Aspect-Oriented Sentiment Analysis from User Reviews of Computer Games

This bachelor's thesis delves into aspect-based sentiment analysis (ABSA) and the creation of a system tailored for examining video game user reviews. By building on established solutions, the system emphasizes the use of generative language models for extracting Aspect-Category-Opinion-Sentiment (ACOS) quadruples. The devised system streamlines the collection and evaluation of reviews, providing an intuitive user interface that enables effortless searching, filtering, and visualization of analytical outcomes via a web application. Furthermore, two datasets predominantly consisting of Czech video game reviews have been assembled

Detection of Pathological Changes in the Aorta during Thoracic Aortic Aneurysm Progression on Molecular Level

The progression of thoracic aortic aneurysm depends on regulation of aortic wall homeostasis and on changes in the structural components of the extracellular matrix, which are affected by multiple molecular signalling pathways. We decided to correlate the diameter of ascending thoracic aneurysm with gene expression of inflammation markers (IL-6, CRP), cytokine receptors (IL-6R, TNFR1, and TNFR2), and extracellular matrix components (Emilin-1, MMP9, and TIMP) for detection of the degree of pathological process of TAA formation. The experimental group was divided into three groups according to the diameter of the aortic aneurysm. Whole blood and tissue samples were properly collected and used for nucleic acid, chromatin, and protein isolation. The mRNA levels were detected by qRT-PCR. For the detection of protein levels a Cytokine Array IV assay kit was used in combination with a biochip analyzer. In aortic tissue, significant positive correlations were found between increased mRNA levels of inflammatory cytokines (CRP and IL-6) on both mRNA levels in tissue and protein from the blood with maximum in stage 3. Changes of gene expression of selected genes can be used for the experimental study of the inflammatory receptor inhibitors during trials targeted on slowing down the progress of aortic wall aneurysm