ABSTRACT We present the results of an ongoing collaboration between computer science and psychology researchers that employs Natural Language Processing (NLP) methods to examine the trajectory of semantic space used during group idea generation sessions. Specifically, we track and estimate the region of semantic space being used and the degree to which new ideas expand that space. We present a visualization of this space mapping endeavor and compare human ratings of creativity dimensions (i.e., novelty, task-relevance, and elaboration) to algorithm-based estimations of those same dimensions. The semantic space mapping and algorithm development projects can be used to deliver real-time feedback to human creative groups in order to optimize the collaborative creativity process. The overall goal of this research is to increase the “survival” of novel ideas and their elaboration in the collaborative ideation and subsequent decision processes.