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.