Searching Social Networks for Subgraph Patterns

被引:1
|
作者
Ogaard, Kirk [1 ]
Kase, Sue [1 ]
Roy, Heather [1 ]
Nagi, Rakesh [2 ]
Sambhoos, Kedar [2 ]
Sudit, Moises [2 ]
机构
[1] US Army Res Lab, Tact Informat Fus Branch, Computat & Informat Sci Directorate, Adelphi, MD 20783 USA
[2] SUNY Buffalo, Dept Ind & Syst Engn, Ctr Multisource Informat Fus, Buffalo, NY USA
关键词
social network analysis; visualization software; graph matching;
D O I
10.1117/12.2015264
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页数:11
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