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Proceedings Paper

Searching social networks for subgraph patterns
Author(s): Kirk Ogaard; Sue Kase; Heather Roy; Rakesh Nagi; Kedar Sambhoos; Moises Sudit
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Paper Abstract

Software tools for Social Network Analysis (SNA) are being developed which support various types of analysis of social networks extracted from social media websites (e.g., Twitter). Once extracted and stored in a database such social networks are amenable to analysis by SNA software. This data analysis often involves searching for occurrences of various subgraph patterns (i.e., graphical representations of entities and relationships). The authors have developed the Graph Matching Toolkit (GMT) which provides an intuitive Graphical User Interface (GUI) for a heuristic graph matching algorithm called the Truncated Search Tree (TruST) algorithm. GMT is a visual interface for graph matching algorithms processing large social networks. GMT enables an analyst to draw a subgraph pattern by using a mouse to select categories and labels for nodes and links from drop-down menus. GMT then executes the TruST algorithm to find the top five occurrences of the subgraph pattern within the social network stored in the database. GMT was tested using a simulated counter-insurgency dataset consisting of cellular phone communications within a populated area of operations in Iraq. The results indicated GMT (when executing the TruST graph matching algorithm) is a time-efficient approach to searching large social networks. GMT’s visual interface to a graph matching algorithm enables intelligence analysts to quickly analyze and summarize the large amounts of data necessary to produce actionable intelligence.

Paper Details

Date Published: 6 June 2013
PDF: 11 pages
Proc. SPIE 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII, 87110T (6 June 2013); doi: 10.1117/12.2015264
Show Author Affiliations
Kirk Ogaard, U.S. Army Research Lab. (United States)
Sue Kase, U.S. Army Research Lab. (United States)
Heather Roy, U.S. Army Research Lab. (United States)
Rakesh Nagi, Univ. at Buffalo, SUNY (United States)
Kedar Sambhoos, Univ. at Buffalo, SUNY (United States)
Moises Sudit, Univ. at Buffalo, SUNY (United States)


Published in SPIE Proceedings Vol. 8711:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII
Edward M. Carapezza, Editor(s)

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