University of Cincinnati Lindner College of Business

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A Framework for Detecting Covert Network Structures in Multilingual Groups

Author(s): Janea Triplett, Andrew Harrison, Brian Mennecke, Akmal Mirsadikov

Status: Published
Year: 2016
Publication Name: Journal of Virtual Worlds Research
Volume: 9, Issue: 2, Page Number(s): 1-21


Abstract

This paper introduces an approach for the examination and organization of unstructured text to identify relationships between networks of individuals. This approach can be used to determine the structure of covert organizations irrespective of the language being used to facilitate conversations between members. This approach uses a simplistic algorithm and does not require an expert understanding of languages or semantics or an a priori knowledge of the network structure for practical application. We present a framework that infers relevant relationships within social network structures using discourse analysis and social network analysis. We test the framework using data collected from a double-blind study to successfully detect the covert structure of three information networks, and their cliques, within an online gaming community during a simulation of a large-scale event.


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