Doctoral Dissertation Research: Impact of Agent-Based Computational Modeling on the Sociological Imagination in an Emerging Academic Field

Rensselaer Polytechnic Institute, Troy NY

Investigators

Abstract

This dissertation research, supported by the Science and Society Program, investigates cultural development in science by focusing on computational social sciences. Scientists and engineers in this emerging international community view their development of cutting-edge computational technologies as a way to envision and catalyze change in the social sciences. This research follows the construction of agent-based computational modeling and simulation, by looking closely at how practices, local settings, narratives, and meanings about the technology are established in the community. The project will include the collection of social network and ethnographic data on the community engaging in agent-based modeling. Social network data are to be gathered from evidence of conference attendance in the community over the last fifteen years, collaboration on conference papers, published manuscripts, modeling projects, participation in online forums, and through individuals' affiliations with research centers, labs, departments, and schools. The ethnographic work is directed at understanding the organizing forces that shape local settings of knowledge production. The literature and discourse of the computational modeling community will also be reviewed and assessed. Finally, agent-based modeling platforms and models are to be evaluated for how these artifacts guide thinking and structure work practice. The main intellectual contribution of this research is to better understand how scientists and engineers organize communities to design computational technology to meet social and moral objectives. A second contribution that this work will make is in further developing the notion of collaborative ethnography when scientists and engineers are at the focus of a study. This collaborative ethnography and the results of the social network analysis may provide an opportunity for members of the computational modeling research community to reflect upon the growth of their field. A potential broader impact of this research is in making the field of computational social science meaningful and more transparent to a wider audience.