Andrew J. Scholand

Modeling interdependencies between power and economic sectors using the N-ABLE agent-based model

The nations electric power sector is highly interdependent with the economic sectors it serves; electric power needs are driven by economic activity while the economy itself depends on reliable and sustainable electric power. To advance higher level understandings of the vulnerabilities that result from these interdependencies and to identify the loss prevention and loss mitigation policies that best serve the nation, the National Infrastructure Simulation and Analysis Center is developing and using N-ABLE{trademark}, an agent-based microeconomic framework and simulation tool that models these interdependencies at the level of collections of individual economic firms. Current projects that capture components of these electric power and economic sector interdependencies illustrate some of the public policy issues that should be addressed for combined power sector reliability and national economic security.

Benefits of synchronous collaboration support for an application-centered analysis team working on complex problems: a case study

A month-long quasi-experiment was conducted using a distributed team responsible for modeling, simulation, and analysis. Six experiments of three different time durations (short, medium, and long) were performed. The primary goal was to discover if synchronous collaboration capability through a particular application improved the ability of the team to form a common mental model of the analysis problem(s) and solution(s). The results indicated that such collaboration capability did improve the formation of common mental models, both in terms of time and quality (i.e., depth of understanding), and that the improvement did not vary by time duration. In addition, common mental models were generally formed by interaction around a shared graphical image, the progress of collaboration was not linear but episodic, and tasks that required drawing and conversing at the same time were difficult to do.

Social language network analysis

In this note we introduce a new methodology that combines tools from social language processing and network analysis to identify socially situated relationships between individuals, even when these relationships are latent or unrecognized. We call this approach social language network analysis (SLNA). We describe the philosophical antecedents of SLNA, the mechanics of preprocessing, processing, and post-processing stages, and the results of applying this approach to a 15-month corporate discussion archive. These example results include an explicit mapping of both the perceived expertise hierarchy and the social support / friendship network within this group.

Assessing group interaction with social language network analysis

In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

Thoughts on critical infrastructure collaboration

In this paper, we describe what we believe to be the characteristics of the collaborations required in the domain of critical infrastructure modeling, based on our experiences to date. We adopt a knowledge management philosophy, which imposes two classes of requirements, contextual who, when, and why), and semantic what interactions are conducted around). We observe that infrastructure models can often engender more insight when used as the basis for a meaningful discussion between the disparate stakeholder groups (private industry, trade organizations, industry lobbying groups, etc.) than when exercised computationally.