Advances in computational systems and methods (parallel, distributed, cloud; agents, networks) are revolutionizing how social science research is done. It is now possible to simulate entire cities, for example, in tremendous detail, not only in terms of technical infrastructures like traffic, but also in terms of the social choices of individuals and how these interact with each other to produce complex phenomena. At the same time, advances in informatics infrastructures mean that more data and more detailed data are collected. These data are not just on our physical environment, but are also along social dimensions. The confluence of these two developments open up many possibilities, and social scientists are now probing questions that they could never ask before. Frequently, asking these questions generate even more inquiry into the interfaces between social science, computer science, information science, and engineering.
In this workshop, we aim to provide a forum for computational social scientists to share advances made in their respective fields, and the innovations they have developed across disciplinary boundaries: on models, methods, data integration and analysis, as well as interpretation of diverse social phenomena. We also hope to foster an environment for earnest dialogue between social scientists keen to employ sophisticated computational models and methods in their research, and computer/information scientists and engineers interested in understanding social science problems.
We invite original research papers on the following topics:
- Modeling methodologies
- Simulation strategies and algorithms
- Organization of heterogeneous social data
- Data-mining and machine learning on social, behavioral, and economic data
- Integration of social data into simulations
- Computational studies of specific social science problems
For more information, please see the workshop website.