A study on Contraction of Similar Questions based on Distance Between Questions in Questionnaire Data

Abstract

Companies often employ questionnaire(s) in order to design marketing strategies or to grasp the trends. Questionnaire data is a large and multi-dimensional data. The authors have analyzed based on visualized results using dimensional reduction and visualization methods such as PCA (Principal Component Analysis) and MDS (Multi-Dimensional Scaling method.) However, if it does not consider the questions which many respondents thought similar meanings, there is a possibility that the characteristics of respondents can not be found out because visualization results are more emphasized by the similar questions than the other ones. This paper defines the distance between questions which represents the similarity of questions, and proposes a method to derive questions having similar meanings for respondents and contract them based on the distance between questions. This paper applies the proposed method to an actual questionnaire data and shows that the features of some groups of respondents can be found while it is difficult in the conventional visualized result.