A platform for mining and visualizing regional collective culture

Abstract

This paper proposes computational methods for mining and visualizing collective culture among the community members of a region. This paper first outlines a procedure to extract significant narratives with text mining technique and spatiotemporal analysis on the textual data transcribed from oral-history interviews with the regional community members. It also introduces the KACHINA-CUBE system that imports the narratives as contextualized fragments of sentences based on spatiotemporal information, visualizes them onto a virtual 3D space, and assist researchers to discover commonalities and diversities among them based on the trajectory equifinality model (TEM), which is a theoretical framework to clarify both the similarities and differences among the trajectories of individual life courses. At the end of this paper, we illustrate a test case on collective culture regarding the once-flourishing film industry in Kyoto. © 2010 Springer-Verlag Berlin Heidelberg.