Kathleen M. Carley

On the robustness of centrality measures under conditions of imperfect data

An analysis is conducted on the robustness of measures of centrality in the face of random error in the network data. We use random networks of varying sizes and densities and subject them (separately) to four kinds of random error in varying amounts. The types of error are edge deletion, node deletion, edge addition, and node addition. The results show that the accuracy of centrality measures declines smoothly and predictably with the amount of error. This suggests that, for random networks and random error, we shall be able to construct confidence intervals around centrality scores. In addition, centrality measures were highly similar in their response to error. Dense networks were the most robust in the face of all kinds of error except edge deletion. For edge deletion, sparse networks were more accurately measured.

Identification of coordination requirements: implications for the Design of collaboration and awareness tools

Task dependencies drive the need to coordinate work activities. We describe a technique for using automatically generated archi-val data to compute coordination requirements, i.e., who must coordinate with whom to get the work done. Analysis of data from a large software development project revealed that coordina-tion requirements were highly volatile, and frequently extended beyond team boundaries. Congruence between coordination re-quirements and coordination activities shortened development time. Developers, particularly the most productive ones, changed their use of electronic communication media over time, achieving higher congruence. We discuss practical implications of our technique for the design of collaborative and awareness tools.

Coding Choices for Textual Analysis: A Comparison of Content Analysis and Map Analysis

Content and map analysis, procedures for coding and understanding texts, are described and contrasted. Where content analysis focuses on the extraction of concepts from texts, map analysis focuses on the extraction of both concepts and the relationships among them. Map analysis thus subsumes content analysis. Coding choices that must be made prior to employing content-analytic procedures are enumerated, as are additional coding choices necessary for employing map-analytic procedures. The discussion focuses on general issues that transcend specific software procedures for coding texts from either a content-analytic or map-analytic perspective.

An approach for relating social structure to cognitive structure

It is proposed that the decision making process is intrinsically formulative in nature; i.e., for the individual the crux of the process is in the development of a frame, a knowledge base, that can be used to make the decision, rather than the evaluation of the alternatives ’per se’. A two stage model of decision making is forwarded. In the first stage the individual develops his frame. This is the critical, formulative, stage and dependent on the socio‐cultural environment. In the second stage the individual makes a decision by evaluating his frame. This stage is mechanical, evaluative, and determined by the frame formulated during the first stage. A consequence of the basic thesis is that the social and cognitive processes can not be decoupled if we are to understand decision making behavior. However, there are few methods currently available that allow the researcher to look at the relationship between the social and the cognitive process. Herein, a set of methods that permit the researcher to look at ...

Computational and mathematical organization theory: perspective and directions

Computational and mathematical organization theory is an interdisciplinary scientific area whose research members focus on developing and testing organizational theory using formal models. The community shares a theoretical view of organizations as collections of processes and intelligent adaptive agents that are task oriented, socially situated, technologically bound, and continuously changing. Behavior within the organization is seen to affect and be affected by the organizations, position in the external environment. The community also shares a methodological orientation toward the use of formal models for developing and testing theory. These models are both computational (e.g., simulation, emulation, expert systems, computer-assisted numerical analysis) and mathematical (e.g., formal logic, matrix algebra, network analysis, discrete and continuous equations). Much of the research in this area falls into four areas: organizational design, organizational learning, organizations and information technology, and organizational evolution and change. Historically, much of the work in this area has been focused on the issue how should organizations be designed. The work in this subarea is cumulative and tied to other subfields within organization theory more generally. The second most developed area is organizational learning. This research, however, is more tied to the work in psychology, cognitive science, and artificial intelligence than to general organization theory. Currently there is increased activity in the subareas of organizations and information technology and organizational evolution and change. Advances in these areas may be made possible by combining network analysis techniques with an information processing approach to organizations. Formal approaches are particularly valuable to all of these areas given the complex adaptive nature of the organizational agents and the complex dynamic nature of the environment faced by these agents and the organizations.

The nature of the social agent

We pose the question, What is necessary to build an artificial social agent? Current theories of cognition provide an analytical tool for peeling away what is understood about individual cognition so as to reveal wherein lies the social. We fractionate a set of agent characteristics to describe a Model Social Agent. The fractionation matrix is, itself, a set of increasingly inclusive models, each one a more adequate description of the social agent required by the social sciences. The fractionation reflects limits to the agents information‐processing capabilities and enrichment of the mental models used by the agent. Together, limited capabilities and enriched models, enable the agent to be social. The resulting fractionation matrix can be used for analytic purposes. We use it to examine two social theories—Festingers Social Comparison Theory and Turners Social Interaction Theory—to determine how social such theories are and from where they derive their social action.

BioWar: scalable agent-based model of bioattacks

While structured by social and institutional networks, disease outbreaks are modulated by physical, economical, technological, communication, health, and governmental infrastructures. To systematically reason about the nature of outbreaks, the potential outcomes of media, prophylaxis, and vaccination campaigns, and the relative value of various early warning devices, social context, and infrastructure, must be considered. Numerical models provide a cost-effective ethical system for reasoning about such events. BioWar, a scalable citywide multiagent network numerical model, is described in this paper. BioWar simulates individuals as agents who are embedded in social, health, and professional networks and tracks the incidence of background and maliciously introduced diseases. In addition to epidemiology, BioWar simulates health-care-seeking behaviors, absenteeism patterns, and pharmaceutical purchases, information useful for syndromic and behavioral surveillance algorithms.

Network Structure in Virtual Organizations

Virtual organizations that use email to communicate and coordinate their work toward a common goal are becoming ubiquitous. However, little is known about how these organizations work. Much prior research suggests that virtual organizations, for the most part because they use information technology to communicate, will be decentralized and non-hierarchical. This paper examines the behavior of one such organization. The analysis is based on a case study of the communication structure and content of communications among members of a virtual organization during a four-month period. We empirically measure the structure of a virtual organization and find evidence of hierarchy. The findings imply that the communication structure of a virtual organization may exhibit different properties on different dimensions of structure. We also examine the relationship among task routineness, organizational structure, and performance. Results indicate that the fit between structure and task routineness affects the perception of performance, but may not affect the actual performance of the organization. Thus, this virtual organization is similar to traditional organizations in some ways and dissimilar in other ways. It was similar to traditional organizations in so far as task-structure fit predicted perceived performance. However, it was dissimilar to traditional organizations in so far as fit did not predict objective performance. To the extent that the virtual organizations may be similar to traditional organizations, existing theories can be expanded to study the structure and perceived performance of virtual organizations. New theories may need to be developed to explain objective performance in virtual organizations.

Cognitive inconsistencies and non-symmetric friendship

Abstract Non-reciprocated relationships, such as all workers knowing the president of the company but only a few of the workers being known by the president, and non-symmetric relationships, such as workers thinking that they know the president and thinking that the president does not know them, are endemic to most social situations. While such inconsistencies may be expected in relationships such as giving advice and lending money, they are rarely expected to occur in seemingly symmetric relationships such as friendship. Nevertheless, they do. We suggest that research in this area has been hampered by the confused language used for describing ‘symmetries’ and ‘non-symmetries’. We present a framework for thinking about these relations that clearly distinguishes cognitive inconsistencies and non-symmetric and non-reciprocated relations. Then, we employ this framework and constructural theory to suggest that owing to cognitive inconsistencies, any interaction-based relationship, including friendship, can potentially be non-symmetric. We examine a series of hypotheses concerning interaction and interaction-based behaviors that derive from this theory using friendship relations. We find that we are able to predict both who is friends with whom, non-symmetry in friendship, and non-reciprocities in the expectation for and recall of friendship.

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.