Data collection is an intrinsic aspect of public opinion research and open-ended questions are a rich source of data on the attitudes, perceptions, and preferences of a population. Open-ended questions allow issues, concerns, and perspectives to surface that the researcher may not have originally considered. In other words, the absence of open-ended questions may result in stones left unturned and, ultimately, biased results. The question remains, however, of how to efficiently and objectively analyze text. Historically, analyzing unstructured text data was a tedious and manual process to read, interpret and code. Today though, the ability to read text data, extract salient concepts and code those concepts has come a very long way, with technology making it possible for the researcher to see and quantify what people are saying. This presentation will present a brief history of text mining technology and peel back the covers on how the technology works. In discussing this, we will also examine what considerations to keep in mind, such as the research effect, and how this process can be applied to public opinion research.