Abstract: A multi-user system for text mining a large population of research documents in an efficient and cost-effective fashion includes a content repository, a text mining processor, and a derived data repository that are linked via a user-accessible, central project manager. The content repository includes a data storage device for storing the research documents and a content selection facility for receiving a user-defined query that is able to support cost-related search parameters. The query is utilized by the content selection facility to select an initial collection of documents from the data storage device. Content spread metrics are then displayed through user-intuitive reports to allow for subsequent modification of the search query to yield an optimized document collection. The optimized document collection is then parsed, tagged and clustered by the text mining processor to produce search results that are stored as a data set in the derived data repository.