In the domain of natural language processing (NLP), a descriptive text-analysis was conducted on the State of the Nation Addresses (SONAs) by South African presidents from 1994 to 2023, employing emotion-and-theme extraction techniques. Sentiment analysis, leveraging two lexicons (AFINN and bing), was applied to gauge the polarity of emotions within the speeches. Concurrently, five topic models were applied, namely Latent Semantic Analysis (LSA), Probabilistic Latent Semantic Analysis (pLSA), Latent Dirichlet Allocation (LDA), Correlated Topic Model (CTM), and Author-Topic Model (ATM), to track thematic patterns.