Guns, Babies and Labor: Campaign Finance Networks in the 2000 Elections (working draft)

This paper seeks to expand upon what we know regarding the structure of interest group networks. To explore the potential for Social Network Analysis in the larger context of group behavior and information sharing, we make use of existing federal contribution data to explore how non-corporate political action committees are linked to one another at the federal level via regulated campaign finance. Thus, we explore the density of networks, who the central players are and group relationships with respect to investment behavior. Here, we make use of FEC contribution data from the 2000 electoral cycle to describe and explore the relationships between the different types of contributions made to federal candidates

Toward an Interoperable Dynamic Network Analysis Toolkit

To facilitate the analysis of real and simulated data on groups, organizations and societies, tools and measures are needed that can handle relational or network data that is multi-mode, multi-link and multi-time period in which nodes and edges have attributes with possible data errors and missing data. The integrated CASOS dynamic network analysis toolkit described in this paper is an interoperable set of scalable software tools. These tools form a toolchain that facilitate the dynamic extraction, analysis, visualization and reasoning about key actors, hidden groups, vulnerabilities and changes in such data at varying levels of fidelity. We present these tools and illustrate their capabilities using data collected from a series of 368 texts on an organizational system interfaced with covert networks in the Middle East

Understanding Terrorist Organizations with a Dynamic Model

Terrorist organizations change over time because of processes such as recruitment and training as well as counter-terrorism (CT) measures, but the effects of these processes are typically studied qualitatively and in separation from each other. Seeking a more quantitative and integrated understanding, we constructed a simple dynamic model where equations describe how these processes change an organization's membership. Analysis of the model yields a number of intuitive as well as novel findings. Most importantly it becomes possible to predict whether counter-terrorism measures would be sufficient to defeat the organization. Furthermore, we can prove in general that an organization would collapse if its strength and its pool of foot soldiers decline simultaneously. In contrast, a simultaneous decline in its strength and its pool of leaders is often insufficient and short-termed. These results and other like them demonstrate the great potential of dynamic models for informing terrorism scholarship and counter-terrorism policy making.Comment: To appear as Springer Lecture Notes in Computer Science v2: vectorized 4 figures, fixed two typos, more detailed bibliograph

Simulating Social Systems Requires Multiple Levels of Complexity ∗

We raise a question of whether it is appropriate to simulate human and social systems using simple ”ant-like ” agents, and argue that in order to simulate emergence and evolution of social order, complexity must reside not only on system level (i.e. simple agents with complex relations), but also on the level of an individual agent, in the form of boundedly rational reasoning and planning capabilities. Further, we show that agent’s ability to socialize with other agents and form informal friendships is key to the emergence of robust organizational structures. These theses are supported by an implemented system that uses a large number of intelligent agents to simulate emergence of terrorist cells and planning and execution of a bomb plot. We demonstrate these emergent behaviours with a detective story that is plausible enough to be published in a newspaper, yet is a completely fictional scenario created and performed by a cast of intelligent agents by means of self-motivation and self-organization. We argue that addition of individual-level realism to the model significantly boosts face validity of the simulation results.

Bouncing back: Recovery mechanisms of covert networks

In study of covert networks and destabilization strategies thereof, much attention has been paid to the task of locating and isolating key individuals within the organization. Metrics such as centrality, betweenness, cognitive load, and others, have all been used for that purpose. The isolation act was considered successful i