In recent years, there has been growing interest in data visualization for text analysis. While text mining and visualization tools have been successfully integrated into research methods in many fields, their use still remains infrequent in mainstream Digital Humanities. Many tools require extensive programming skills, which can be a roadblock for some literary scholars. Furthermore, while some visualization tools provide graphical user interfaces, many humanities researchers desire more interactive and user-friendly control of their data. In this talk we introduce the Interactive Text Mining Suite (ITMS), an application designed to facilitate visual exploration of digital collections. ITMS provides a dynamic interface for performing topic modeling, cluster detection, and frequency analysis. With this application, users gain control over model selection, text segmentation as well as graphical representation. Given the considerable variation in literary genres, we have also designed our graphical user interface to reflect choice of studies: scholarly articles, literary genre, and sociolinguistic studies. For documents with metadata we include tools to extract the metadata for further analysis. Development with the Shiny web framework provides a set of clean user interfaces, hopefully freeing researchers from the limitations of memory or platform dependency.