Latin is difficult for machines to translate due to the language being highly inflectional and overlapping word forms frequently creating ambiguity. Even with the help of dedicated human translators, it is difficult to grasp the motivations and nuances of the works of many Ancient Roman authors without additional annotations and readers’ notes. Using natural language processing (NLP) and semantic vector analysis, I have gathered a list of keywords that represent significant themes in Ancient Roman culture and found each of their most associated words in the works of Vergil, Ovid, and Julius Caesar. After analyzing the words that returned as the most similar, I found that many of them are not direct synonyms; instead, they indicate the use of symbolism and figurative language, and the existence of important implicit cultural themes related to these keywords. The knowledge of these nuances would surely help readers better understand the context and motivations of these texts and figures. This methodology can be applied for further exploration of other keywords or other notable ancient literature. The combination of modern NLP practices and old Latin texts present a new and unique perspective and analytic tool: this multifaceted framework can be extended to other spheres and present more fascinating findings in the realm of the digital humanities.