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Abstract

This research draws on longitudinal network data from an online community to examine patterns of users' behavior and social interaction, and infer the processes underpinning dynamics of system use. The online community represents a prototypical example of a complex evolving social network in which connections between users are established over time by online messages. We study the evolution of a variety of properties since the inception of the system, including how users create, reciprocate, and deepen relationships with one another, variations in users' gregariousness and popularity, reachability and typical distances among users, and the degree of local redundancy in the system. Results indicate that the system is a small world characterized by the emergence, in its early stages, of a hub-dominated structure with heterogeneity in users' behavior. We investigate whether hubs are responsible for holding the system together and facilitating information flow, examine first-mover advantages underpinning users' ability to rise to system prominence, and uncover gender differences in users' gregariousness, popularity, and local redundancy. We discuss the implications of the results for research on system use and evolving social networks, and for a host of applications, including information diffusion, communities of practice, and the security and robustness of information systems.

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Abstract

The capability to build nuclear weapons is a key national security factor that has a profound influence on the balance of international relations. In addition to longstanding players, regional powers and peripheral countries have sought for ways of acquiring and/or developing them. The authors postulate that to express the capabilities, relative positions, and interrelations of the countries involved in the production of nuclear weaponization knowledge, dynamic network analysis provides valuable insight. In this article, the authors use a computational framework that combines techniques from dynamic network analysis and text mining to mine and analyze large-scale networks that are extracted from open theoretical and experimental nuclear research publications of the last two decades. More specifically, they build interlinked, dynamic networks that model relationships of nuclear researchers based on the open literature and supplement this information with text mining to classify the nuclear weaponization capabilities of each publication-of each author, organization, city, and country. Using such a comprehensive computational framework, they are able to (a) elicit the hot topics in nuclear weaponization research, (b) assess the nuclear expertise level of each country, (c) differentiate between established and emergent players, and (d) identify the key entities at various levels such as organization, city, and country.