Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

This white paper makes a case for Sandia National Laboratories investments in complex adaptive systems science and technology (S&T) -- investments that could enable higher-value-added and more-robustly-engineered solutions to challenges of importance to Sandia's national security mission and to the nation. Complex adaptive systems are ubiquitous in Sandia's national security mission areas. We often ignore the adaptive complexity of these systems by narrowing our 'aperture of concern' to systems or subsystems with a limited range of function exposed to a limited range of environments over limited periods of time. But by widening our aperture of concern we could increase our impact considerably. To do so, the science and technology of complex adaptive systems must mature considerably. Despite an explosion of interest outside of Sandia, however, that science and technology is still in its youth. What has been missing is contact with real (rather than model) systems and real domain-area detail. With its center-of-gravity as an engineering laboratory, Sandia's has made considerable progress applying existing science and technology to real complex adaptive systems. It has focused much less, however, on advancing the science and technology itself. But its close contact with real systems and real domain-area detail represents a powerful strength with which to help complex adaptive systems science and technology mature. Sandia is thus both a prime beneficiary of, as well as potentially a prime contributor to, complex adaptive systems science and technology. Building a productive program in complex adaptive systems science and technology at Sandia will not be trivial, but a credible path can be envisioned: in the short run, continue to apply existing science and technology to real domain-area complex adaptive systems; in the medium run, jump-start the creation of new science and technology capability through Sandia's Laboratory Directed Research and Development program; and in the long run, inculcate an awareness at the Department of Energy of the importance of supporting complex adaptive systems science through its Office of Science.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

There is considerable interest in developing predictive capabilities for social diffusion processes, for instance enabling early identification of contentious "triggering" incidents that are likely to grow into large, self-sustaining mobilization events. Recently we have shown, using theoretical analysis, that the dynamics of social diffusion may depend crucially upon the interactions of social network communities, that is, densely connected groupings of individuals which have only relatively few links to other groups. This paper presents an empirical investigation of two hypotheses which follow from this finding: 1.) the presence of even just a few inter-community links can make diffusion activity in one community a significant predictor of activity in otherwise disparate communities and 2.) very early dispersion of a diffusion process across network communities is a reliable early indicator that the diffusion will ultimately involve a substantial number of individuals. We explore these hypotheses with case studies involving emergence of the Swedish Social Democratic Party at the turn of the 20th century, the spread of SARS in 2002-2003, and blogging dynamics associated with potentially incendiary real world occurrences. These empirical studies demonstrate that network community-based diffusion metrics do indeed possess predictive power, and in fact can be significantly more predictive than standard measures. © 2010 IEEE.

The research described in this report developed the theoretical and conceptual framework for understanding, recognizing, and anticipating the origins, dynamic mechanisms, perceptions, and social structures of Islamic social reform movements in the Muslim homeland and in diaspora communities. This research has revealed valuable insights into the dynamic mechanisms associated with reform movements and, as such, offers the potential to provide indications and warnings of impending violence. This study produced the following significant findings: (1) A framework for understanding Islamic radicalization in the context of Social Movement Theory was developed and implemented. This framework provides a causal structure for the interrelationships among the myriad features of a social movement. (2) The degree to which movement-related activity shows early diffusion across multiple social contexts is a powerful distinguisher of successful and unsuccessful social movements. Indeed, this measurable appears to have significantly more predictive power than volume of such activity and also more power than various system intrinsics. (3) Significant social movements can occur only if both the intra-context 'infectivity' of the movement exceeds a certain threshold and the inter-context interactions associated with the movement occur with a frequency that is larger than another threshold. Note that this is reminiscent of, and significantly extends, well-known results for epidemic thresholds in disease propagation models. (4) More in-depth content analysis of blogs through the lens of Argumentation Theory has the potential to reveal new insights into radicalization in the context of Social Movement Theory. This connection has the potential to be of value from two important perspectives - first, this connection has the potential to provide more in depth insights into the forces underlying the emergence of radical behavior and second, this connection may provide insights into how to use the blogosphere to influence the emergent dialog to effectively impact the resulting actions taken by the potential radicals. The authors of this report recognize that Islamic communities are not the only source of radicalism; indeed many other groups, religious and otherwise, have used and continue to use, radicalism to achieve their ends. Further, the authors also recognize that not all Muslims use, or condone the use of, radical behavior. Indeed, only a very small segment of the Muslim communities throughout the world use and/or support such behavior. Nevertheless, the focus of this research is, indeed, on understanding, recognizing, and anticipating the origins, dynamic mechanisms, perceptions, and social structures of Islamic radicalism.

Abstract not provided.

Abstract not provided.

This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.

Abstract not provided.