Lewis, E.T., Carley, K.M., & Diesner, J. (2003). Displaying Responsiveness or Asserting Identity in Organizational Language: How Concept Networks Capture Rhetorical Strategies.

Network Text Analysis supports analysts in detecting the organizational structure of covert networks from textual data. We have formalized an approach for Network Text Analysis and implemented it into a software package referred to as AutoMap. We will report on the extraction of the organizational structure of three covert networks, which are Hamas, Al-Qaeda and Jamaah Islamiyah, with AutoMap. For each of the three groups we have one corpus with about 550 texts that were collected from a variety of sources such as LexisNexis, trial transcripts and research papers. The network data that we extracted from the corpora is multi-mode, multi-link, and multi-time period, and has attributes of nodes and edges. We will present results of the network analysis of the extracted data such as the identification of critical individuals in the networks and their linkage to knowledge, resources and other organizations, and compare the revealed structures in order to identify idiosyncrasies of each group. The network analysis was performed with ORA, a statistical toolkit for network analysis.