Extraction of important keywords in free text of questionnaire data and visualization of relationship among sentences

Recently, companies often carry out questionnaire(s) and develop marketing strategies. There are usually two types of forms for the answer of a questionnaire. One is the form to select prepared answers and the other is free text form. The true message might be in the text form rather than the numerical part, then the analysis of free text form is needed. The amount of text in a questionnaire is, however, usually large and difficult to read whole text data for analysis. This study tries to develop a free text analysis support system which visualizes relationships among respondents based on their texts and shows their opinions using graph structure of keywords. First, this paper proposes the extraction method of important keywords in their opinions based on the modification relationships. Next, it clusters the respondents interactively on visible space using MDS. Finally, it shows their opinions using HK Graph which can visualize the relationship among words with hierarchical network structure based on the co-occurrence information for the keyword graph.