Revealing Social Structure from Texts: Meta-Matrix Text Analysis as a Novel Method for Network Text Analysis

Revealing Social Structure from Texts: Meta-Matrix Text Analysis as a Novel Method for Network Text Analysis

Jana Diesner (Carnegie Mellon University, USA) and Kathleen M. Carley (Carnegie Mellon University, USA)
Copyright: © 2005 |Pages: 28
DOI: 10.4018/978-1-59140-396-8.ch004
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Abstract

Texts can be coded and analyzed as networks of concepts often referred to as maps or semantic networks. In such networks, for many texts there are elements of social structure — the connections among people, organizations, and events. Within organizational and social network theory an approach called the meta-matrix is used to describe social structure in terms of the network of connections among people, organizations, knowledge, resources, and tasks. We propose a combined approach using the meta-matrix model, as an ontology, to lend a second level of organization to the networks of concepts recovered from texts. We have formalized and operationalized this approach in an automated tool for text analysis. We demonstrate how this approach enables not only meaning but also social structure to be revealed through text analysis. We illustrate this approach by showing how it can be used to discover the social structure of covert networks — the terrorist groups operating in the West Bank.

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