PC Magazine published a February 27 article “The Online Hunt for Terrorists.” It focuses on the work of the Artificial Intelligence Laboratory at the University of Arizona, and in particular their Dark Web project. In my recent post “Military Social Media Intelligence“, I categorized part of the US military effort in social media as focusing on reconnaisance efforts, and the work going in this laboratory covers the length and breadth of the subject nicely.
Essentially, the Dark Web system is a collection of spidering tools for crawling and indexing content from websites, forums, blogs, and video and audio media to collect counter-terrorism intelligence. It benefits from the fact that not only do terrorists tend to discuss a certain portion of their internal activities in publicly accessible online settings, but that key communities, individuals, and their connections can be identified from social media content both central and peripheral to actual terrorism groups.
What I like is how comprehensively their system tackles social media analytics for this purpose:
- Social network analysis - identifying communities and groups
- Content (semantic) analysis and categorization
- Citation / co-authoriation analysis (a form of network analysis)
- Sentiment analysis (albeit a specialized form focusing on levels of violence)
- Authorship profiling and identification (de-anonymization)
- Video and audio mining
Of course, their work isn’t limited to middle eastern terrorist group activities, but domestic terrorism as well. Here’s a little terrorist network visualization that the Dark Web system generated automatically (see link for citation). While it’s not a terribly sophisticated graphic, what’s important is the resulting intelligence and how it was achieved:
The PC Magazine article is also interesting as it also captures the debate between automated analysis and human-mediated analysis similar to that seen in marketing and public relations. While manual analysis could never filter through the millions of posts that automated systems can process efficiently, many experts maintain that expert analysis provides more insightful and deep results than automation ever will.
However, nobody’s arguing against the pairing of social media analytics (such as the Dark Web system) with human research as the best of both worlds.
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