By Eric Sauda and Alireza Karduni
Architects and designers have recently become interested in the use of “big data”. The most common paradigm guiding this work is the optimization of a limited number of factors, e.g. façade designs maximizing light distribution. For most design problems, however, such optimization is oversimplified and reductive; the goal of design is the discovery of possibilities in conditions of complexity and uncertainty. This paper studies the use of Twitter as an extended case study for uncovering different methods for the analysis of urban social data, concluding that a visual analytic system that uses a knowledge generation approach is the best option to flexibly and effectively explore and understand large multidimensional urban datasets.
