DOI: 10.18178/wcse.2025.06.013
Filipino Genz Slang Sentiment Analyzer using BERT
Abstract— The rapid evolution of online communication has led to the emergence of Filipino Gen Z slang, a dynamic and evolving linguistic phenomenon. Traditional sentiment analysis models often struggle with understanding these slang expressions, necessitating the development of a more specialized approach. This study explores the application of BERT-based model to recognize and analyze sentiment in Filipino Gen Z slang. The model is fine-tuned using a curated dataset of slang expressions to improve accuracy in sentiment classification. Additionally, the research contributes to the advancement of natural language processing (NLP) in low-resource languages and offers insights into modern Filipino digital communication. The results demonstrate the effectiveness of transformer-based architecture in capturing the nuances of Filipino Gen Z slang, providing a more context-aware sentiment analysis tool.
Index Terms— GenZ slang, sentiment analysis, BERT, NLP, deep learning, transformer models.
Ria A. Sagum, Mark Ciedrick A. Ramos, Diana Rose A. Certeza, Alijah Czareen A. Andres, Aaronn Daphne M. Gatchalian
Polytechnic University of the Philippines, PHILIPPINES
Cite: Ria A. Sagum, Mark Ciedrick A. Ramos, Diana Rose A. Certeza, Alijah Czareen A. Andres, Aaronn Daphne M. Gatchalian, "Filipino Genz Slang Sentiment Analyzer using BERT", 2025 the 15th International Workshop on Computer Science and Engineering (WCSE 2025), pp. 78-83, Jeju Island, South Korea, June 28-30, 2025.