Man-Machine Interface of a Support System for Analyzing Open-Ended Questionnaires

Abstract

This paper proposes man-machine interface of support system for analyzing answers to open-ended questions supplied by customers of the mobile game content reply when they unsubscribe from the services. Since open-ended questions, however, place no restrictions on descriptions, the answers include an enormous amount of text data for the content provider. It is time-consuming to read all of the texts one by one. Since a large number of answers are identical to choices included in the multiple-choice questions or unnecessary opinions unconcerned with the game, there are few answers that should be read. Most opinions are needed to know only the number and the outline. However, the provider should not omit to read the unexpected opinion that is a minority. Additionally, since answers are input through cellular phones, they often include many symbols dependent on various kinds of terminals and grammatical mistakes, making them hard to understand. Our research, therefore, aims to create a system that supports the provider to analyze the answers of open-ended questions efficiently. The main function of the support system divides the answers into typical opinions and atypical opinions. Divided opinions are presented with different user interfaces, because the content providers can analyze the two type opinions with each way.