Gender stereotypes have endured despite substantial change in gender roles. Previous work has assessed how gender stereotypes affect language production in particular interactional contexts. Here, we assessed communication biases where context was less specified: written texts to diffuse audiences. We used Latent Semantic Analysis (LSA) to computationally quantify the similarity in meaning between gendered names and stereotype-linked terms in these communications. This revealed that female names were more similar in meaning to the proscriptive (undesirable) masculine terms, such as emotional.