Pressible is a school blogging and content management system developed by EdLab at Teachers College Columbia University, with over three thousand community users and more than five hundred blogs. In this paper, social network analysis and natural language processing with Latent Dirichlet Allocation topic model approaches were utilized to gain insights into Pressible, to explore four developmental stages of a college-wide social network and their associations with blog content creation. The results showed that professors who developed courses through Pressible became the most influential persons in the learning network on this blogging system. Students joined the online discussions by engaging with the course blogs to become influencers in the learning network. Students extended the online discussion topics beyond the scope of course topic set by professors. The topic cooccurrence frequencies of individuals increase as the whole learning network had more active members and connections during a rapid growth stage.