This research seeks to improve collaborative analysis in fields such as criminal justice, intelligence, and epidemiology by developing tools that capture and represent essential elements of analytic conversations. The work has three major aims: (a) understanding how team hypotheses, insights, and problem orientation are reflected in their conversations; (b) developing and testing natural language processing (NLP) techniques to detect teams? hypotheses, insights, and problem orientation; and (c) developing and testing methods to communicate the results of NLP analyses to provide teams with feedback on their own and other teams? reasoning processes. These goals are addressed through behavioral studies, NLP research, and tool development and evaluation. Intellectual merit: The project provides unique contributions in four areas: (a) understanding how team analytical processes are evidenced in team communication; (b) advancing the state-of-the art in NLP by developing discourse analysis techniques for use in collaborative analysis applications; (c) applying NLP techniques to the support of team analytical processes; and (d) designing interfaces to provide feedback within and across teams. The research also furthers the training and education of undergraduate and graduate students. Broader impact: The project has the potential to improve collaborative investigative analysis in many fields of critical importance to society, including criminal justice, intelligence, science, and epidemiology. The results will provide new tools for analysts, recommendations for organizational practices to improve the quality of collaborative analysis, new methods for training professional analysts, and new learning tools for graduate programs in fields such as epidemiological analysis and criminal justice.
