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Text mining, though still a nascent industry, has been growing quickly along with the awareness of the importance of unstructured data in business analytics, customer retention and extension, social media, and legal applications. There has been a recent increase in the number of commercial text mining product and service offerings, but successful or wide-spread deployments are rare, mainly due to a dependence on the expertise and skill of practitioners. Accordingly, there is a growing need for re-usable repositories for text mining. In this paper, we focus on dictionary-based text mining and its role in enabling practitioners in understanding and analyzing large text datasets. We motivate and define the problem of exploratory dictionary construction for capturing concepts of interest, and propose a framework for efficient construction, tuning, and re-use of these dictionaries across datasets. The construction framework …