Adversary phase change detection using S.O.M. and text data

Digital Signal Processing Workshop and IEEE Signal Processing Education Workshop(2011)

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摘要
In this work, we developed a self-organizing map (SOM) technique for using web-based text analysis to forecast when a group is undergoing a phase change. By “phase change”, we mean that an organization has fundamentally shifted attitudes or behaviors. For instance, when ice melts into water, the characteristics of the substance change. A formerly peaceful group may suddenly adopt violence, or a violent organization may unexpectedly agree to a ceasefire. SOM techniques were used to analyze text obtained from organization postings on the world-wide web. Results suggest it may be possible to forecast phase changes, and determine if an example of writing can be attributed to a group of interest.
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关键词
internet,data handling,self-organising feature maps,text analysis,som,web based text analysis,phase change detection,selforganizing map technique,text data,world wide web,testing,attitudes,elementary particles,government,classification algorithms,web pages,phase change,processing,writing,water
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