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This repository explores how Rappler articles shape presidential policies by analyzing dominant themes related to President Bongbong Marcos' first year in office using Latent Semantic Analysis (LSA). The study provides insights for policy-making, strategic communications, and public engagement.
This repository provides an implementation of topic modelling techniques, namely Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA), specifically designed for analyzing news articles.
Latent Semantic Analysis applied on movies, both in a content-based approach (exploiting the movies overviews) and in a collaborative approach (exploiting the users rates)