Sentiment Analysis of Anti-LGBTQ+ laws in Brazil using Comparative Analysis Models

Pscheidt, Giorgia Luzia (2023) Sentiment Analysis of Anti-LGBTQ+ laws in Brazil using Comparative Analysis Models. Masters thesis, Dublin, National College of Ireland.

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Abstract

Social media has become an important platform when it comes to expressing opinions, which means it can be used as a valuable tool for understanding critical points regarding political sentiment. This research wants to explore the sentiment analysis on online discussions related to anti-LGBTQ+ laws being released around the world and the potential impact in Brazilians opinions since past events involving homophobia and prejudice. This study uses data analysis techniques, such as web scraping, machine learning and deep learning models to collect, analyse the sentiments and find insights based on translated comments about anti-LGBTQ+ laws videos circulating in the news channels on YouTube. The literature review shows the studies around sentiment analysis using machine learning and use of multilingual approaches and the challenges faced. The results of the research shows that the negative and positive classes are well labelled by the models but struggles with the neutral due to spam comments and not enough labelled data.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Staikopoulos, Athanasios UNSPECIFIED
Uncontrolled Keywords:	Sentiment analysis; anti-LGBTQ+ laws; YouTube comments; machine learning; data analysis
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HV Social pathology. Social and public welfare > Discrimination Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks H Social Sciences > HQ The family. Marriage. Woman > Sexual life > Sexual minorities
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	20 May 2025 16:17
Last Modified:	20 May 2025 16:17
URI:	https://norma.ncirl.ie/id/eprint/7593

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