Social Science Modeling and Visualization
Social Science Modeling and Information Visualization Workshop.
Author | Editor: Canna, S. & Popp, R. (NSI, Inc).
The Social Science Modeling and Information Visualization Workshop provided a unique forum for bringing together leading social scientists, researchers, modelers, and government stakeholders in one room to discuss the state-of-the-art and the future of quantitative/computational social science (Q/CSS) modeling and information visualization. Interdisciplinary quantitative and computational social science methods from mathematics, statistics, economics, political science, cultural anthropology, sociology, neuroscience, and modeling and simulation – coupled with advanced visualization techniques such as visual analytics – provide analysts and commanders with a needed means for understanding the cultures, motivations, intentions, opinions, perceptions, and people in troubled regions of the world.
Military commanders require means for detecting and anticipating long-term strategic instability. They have to get ahead and stay ahead of conflicts, whether those conflicts are within nation states, between nation states, and/or between non-nation states. In establishing or maintaining security in a region, cooperation and planning by the regional combatant commander is vital. It requires analysis of long-term strategic objectives in partnership with the regional nation states. Innovative tools provided by the quantitative and computational social sciences will enable military commanders to both prevent conflict and manage its aftermath when it does occur.
The need for interdisciplinary coordination among the academic, private, and public sectors, as well as interagency coordination among federal organizations, is critical to solving the strategic threat posed by dynamic and socially complex threats. Mitigating these threats requires applying quantitative and computational social sciences that offer a wide range of nonlinear mathematical and nondeterministic computational theories and models for investigating human social phenomena. Moreover, advanced visualization techniques are also critical to help elucidate – visually – complex socio-cultural situations and possible courses of action under consideration by decision-makers.
These social science modeling and visualization techniques apply at multiple levels of analysis, from cognition to strategic decision-making. They allow forecasts about conflict and cooperation to be understood at all levels of data aggregation from the individual to groups, tribes, societies, nation states, and the globe. These analytic techniques use the equations and algorithms of dynamical systems and visual analytics, and are based on models: models of reactions to external influences, models of reactions to deliberate actions, and stochastic models that inject uncertainties. Continued research in the areas of social science modeling and visualization are vital. However, the product of these research efforts can only be as good as the models, theories, and tools that underlie the effort.
The Department of Defense (DoD) and Department of Homeland Security (DHS) have responded to these needs and new developments in the field of quantitative/computational social science modeling and visualization by changing their orientation to social and cultural problems. While these efforts would not have been funded several years ago, they are cautiously being explored and supported today. The DoD and DHS have and continue to embrace this research area – through an iterative, spiral process where they will build a little, then learn a little – until there is a strong foundation for supporting the social sciences. The DoD and DHS have also broadened their horizons by looking outside the US Government (USG) to understand and mitigate threats by engaging corporations, non-profit organizations, centers of excellence, and academia. The DoD and DHS have recognized the need to respond to a new type of adversarial interaction. Current and future operations demand the capability to understand the social and cultural terrain and the various dimensions of human behavior within this terrain. This evolution will require a re-examination of DoD and DHS actions such as developing non-kinetic capabilities and increasing interagency coordination.
While the DoD and DHS are changing their orientation to quantitative/computational social science modeling, difficulties and challenges remain. First, opportunities and challenges in the theoretical domain include the need for better, scientifically grounded theories to explain socio-cultural phenomena related to national security. Better theories affect modeling on all levels. They yield clarified assumptions, better problem scoping and data collection, a common language to interpret analysis, and inform visualization options. Quantitative/computational social science presents the opportunity to integrate theories, explore their applicability, and test their validity.
A second challenge facing the social science modeling community is the need to clearly frame the core question. This is a step that is often overlooked in the creation of new social science models. The model’s intent must be clearly defined from the start. If the model is not framed correctly and if the assumptions, limitations, and anticipated outcomes of the model are not clear, the field of social science modeling can be easily tarnished. Part of the problem is the ambiguous and widespread use of the word “culture,” which can be used to mean many things. This term must be better defined and normalized to assist modelers in framing the problem.
The third challenge is the lack of strong datasets for social science researchers. Available datasets may either lack a strong methodology or be unavailable to the open source community. Additionally, because social, cultural, and behavioral issues have only recently come to the attention of policy- and decision-makers, data remains relatively sparse. New efforts and investment in strong datasets are required to fuel the progress of quantitative/computational social science.
Fourth, the USG must adapt to the open-source nature of many social, cultural, and behavioral issues of interest to the defense, homeland security, and intelligence community today. Not only do cleared facilities restrict the access of many researchers and subject matter experts, they also restrict the type of data that can be used and the distribution of the model’s output. Ultimately, open source will become the main source of socio-cultural information, and the USG must create environments for these developments to occur.
Finally, visualization should not be considered solely as the final step in the creation of a social science model; it must be considered from the very beginning. It is a form of analytic output that adds depth, value, and utility to an effort. Furthermore, visualization can be used for more than just analysis; it can also be used to evaluate data. Visualization is the means through which analysts and commanders receive and understand data. Its value should not be left as an afterthought.
The degree of interest and understanding in quantitative/computational social science exhibited by government stakeholders are higher than they have ever been before. New efforts at interagency coordination, particularly between the DoD and DHS are signs of the importance of this field. Likewise, the level of interest and enthusiasm shown by academia in participating in these efforts is unprecedented. The coalescing need for timely, accurate, socio-cultural modeling and visualization tools is growing to such an extent that calls for a concept of operations are emerging. However, further cooperation is needed across the USG to advance, guide, and shape the science and meet the growing need for socio-cultural understanding.
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