ABSTRACT
This research is an ongoing software development effort that uses neural networks to map word relations, hierarchies, gaps, and foci of terms within large data sets of architecture theory and public opinion, as they are graphed geographically and by epoch. It seeks to develop a set of digital tools capable of engaging with the massive amounts of public opinions, debates, and beliefs that compose our ideological landscapes, as they become topics relevant to the built environment. It is meant as a higher resolution layer of analysis in order to increase our capacity to map and understand urban experiences and occupation patterns, with the purpose of modulating struggles between environmental and human forces in culturally sensitive ways.
