Mining open answers in questionnaire data

Abstract

Surveys are important tools for marketing and for managing customer relationships; the answers to open-ended questions, in particular, often contain valuable information and provide an important basis for business decisions. The summaries that human analysts make of these open answers, however, tend to rely too much on intuition and so aren't satisfactorily reliable. Moreover, because the Web makes it so easy to take surveys and solicit comments, companies are finding themselves inundated with data from questionnaires and other sources. Handling it all manually would be not only cumbersome but also costly. Thus, devising a computer system that can automatically mine useful information from open answers has become an important issue. We have developed a survey analysis system that works on these principles. The system mines open answers through two statistical learning techniques: rule learning (which we call rule analysis) and correspondence analysis.