The Content Structure of Intelligence Reports

Despite its close connection to many of the methodological questions and problems related to uncloaking hidden structures or to analyzing network dynamics tackled by network analysts in tterrorism or crime studies, researchers on Cold War intelligence have shown limited interest in network analysis. Although there might be material-related reasons for that, the resistance is to a great extent caused by the unfamiliarity with the method itself. Following the idea that how one looks at the material determines what they see, this article will evidence how social network analysis could be applied to historical sources in order to extract, analyze and visualize new knowledge. The analysis will illustrate the capability of SNA-based keyword co-occurrence network analysis and visualizations for uncovering and identifying the corpus’ structural properties, detecting the thematic backbone of the report corpus, and for analyzing network dynamics. The material used in the analysis consists of reports on Nordic affairs produced in 1975-1989 by the East German foreign intelligence service. Besides keyword co-occurrence network analysis and visualizations, the article shows how community detection techniques can be used to extract thematic backbones in a report corpus. A critical assessment of the results obtained by SNA techniques in their historical context confirms their validity and reliability. More generally, the results showed that combining SNA with methods of content analysis offers a promising perspective for developing new research methods for the analysis of the social network of language capable of tackling and extracting contextual and semantic relationships in networks based on textual data. Furthermore, the SNA-based approach to textual networks could open up new perspectives for exploratory historical research with the view to finding new foci for research and comprehending new research hypothesis and questions.