Dr. Martina Morris (PI) & Dr. Mark Handcock at the Center for Studies in Demography and Ecology of University of Washington are funding a SoNIA-related project contract to integrate dynamic network visualization techniques with the R statnet package developed by Morris, Handcock, et al at the CSDE. The funds come from the NIH grants supporting the Network Modeling Project at the University of Washington (grants R01 HD41877 and R01 DA12831)
The focus is on adapting and developing visualization techniques for dynamic network data. The specific emphasis will be on techniques relevant for understanding:
a) infectious disease transmission (change in state of elements due to a network diffusion process) and
b) the stationary dynamics (model-based addition and removal of nodes/edges) of longitudinal network data and simulation output.
The goal is to develop robust, rigorous and repeatable procedures for visually interpreting time-based network data. We will achieve this by linking existing software components and improving existing techniques to generate animations and export movies from R or other statistical packages into standard formats suitable for use in presentations or websites.
SoNIA is a Java-based package for visualizing dynamic or longitudinal “network” data. By dynamic, we mean that in addition to information about the relations (ties) between various entities (actors, nodes) there is also information about when these relations occur, or at least the relative order in which they occur.
At the same time that I’ve been doing the literature research for this project, I’ve also been conducting a short term longitudinal study of social and informational networks as they develop among the entering first-year students of the Class of ’04 and the rest of the Bennington College community. I had several reasons for wanting to do this. Throughout this work I have been discussing and suggesting conceptual frameworks for thinking about information in social networks. My hope was that doing this kind of study might give me some real data for comparison – a qualitative check on how well theory actually describes what is going on. Ideally a network study of the campus might give me a baseline idea of the social structure of Bennington which could be built upon in future work. At the very least, attempting to construct and implement a study would teach me a great deal about methodologies and the complicating factors which will inevitably crop up when dealing with theory and data in the real world.
Dr. Martina Morris (PI) & Dr. Mark Handcock at the Center for Studies in Demography and Ecology of University of Washington are funding a SoNIA-related project contract to integrate dynamic network visualization techniques with the R statnet package developed by Morris, Handcock, et al at the CSDE. The funds come from the NIH grants supporting the Network Modeling Project at the University of Washington (grants R01 HD41877 and R01 DA12831)