Conceptual graph generation from text documents based on perceptual balance

A conceptual graph generation method is proposed in this paper. A conceptual graph is useful for studying human verbal caring interactions such as counseling, based on an interpersonal psychological approach referred to as ´naive psychology´. We apply the visual assessment of clustering tendency (VAT) to naive psychology, with particular reference to the visual understanding of people. A conceptual graph is constructed from words and sentences selected by morphological analysis. Furthermore, the VAT algorithm produces a visual display that can be used to assess clustering tendencies in a set of persons (notions) by reconstructing a digital image representation of a square relational dissimilarity matrix. This algorithm clearly represents two types of imbalanced situations in naive psychology: namely the crisp and fuzzy situations. In addition, social simulations that utilize several graphs are introduced.