{"id":10236,"date":"2025-09-08T13:40:30","date_gmt":"2025-09-08T17:40:30","guid":{"rendered":"https:\/\/portfolios.cs.earlham.edu\/?page_id=10236"},"modified":"2025-12-14T12:11:35","modified_gmt":"2025-12-14T17:11:35","slug":"helena-jose","status":"publish","type":"page","link":"https:\/\/portfolios.cs.earlham.edu\/index.php\/students\/2024-2\/cs488\/helena-jose\/","title":{"rendered":"Helena Aleluya Jose – Quantifying Themes in Theatre Using Topic Modeling (LDA)"},"content":{"rendered":"\n
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Introduction<\/h2>\n\n\n\n
My name is Helena Aleluya Jos\u00e9, and I\u2019m an international student from Angola. I\u2019m also a Computer Science and Theater double major, and an African and African-American Studies and Creative Writing double minor. As both a computer scientist and a playwright, I wanted to create a project that reflects the intersection of my passions. For my senior capstone, I developed a framework that applies topic modeling techniques (LDA) to a corpus of dramatic texts in order to identify and compare thematic patterns across plays.<\/p>\n\n\n\n
Abstract<\/h3>\n\n\n\n
This capstone project aims to develop a novel approach for analyzing and comparing playwrights\u2019 unique voices and styles by applying topic modeling techniques, specifically Latent Dirichlet Allocation (LDA), on a corpus of theater texts. By leveraging advanced natural language processing (NLP) methods, the project will preprocess and prepare a diverse collection of plays for topic modeling, implement custom algorithms tailored for dramatic literature, and analyze the discovered topics to identify recurring themes, character archetypes, and narrative structures prevalent across different playwrights\u2019 works. Interactive visualization tools will be developed to facilitate the exploration and interpretation of these insights, enabling literary scholars and critics to understand the creative processes better and the influences that shape dramatists\u2019 voices.<\/p>\n\n\n\n
Keywords<\/strong> <\/p>\n\n\n\n
Topic modeling techniques, textual analysis, LDA model, Digital Humanities<\/p>\n\n\n\n
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