Text is a vehicle to convey information that reflects the writer’s linguistic style and communication patterns. By studying these attributes, we can discover latent insights about the author and their underlying message. This article uses such an approach to better understand patent applications and their inventors. While prior research focuses on patent metadata (i.e., filing year or gendered inventor names), we employ machine learning and natural language processing to extract hidden informati