The Challenge
Radicalization is on the rise, with extremist groups using social media to communicate and recruit on a global scale. Established members may be outspoken and highly visible, but new and emerging members are more difficult to spot. The burning question: Is there a way to identify these people before it’s too late?
We exlpored how Open Source Intelligence could provide a powerful response, involving advanced machine learning techniques to explore social media, analyse content, and ultimately discover persons or patterns of interest.
What was Involved
An analytical proof of concept was completed in 2016 by focusing on a specific use-case involving detecting extremist behaviour on Twitter, however the tools developed during this time could be adopted to many other use-cases and scenarios. I led the design and development for the graphical storyboard and video using data visualisations to help explain the technical approach and demonstrate the radicalization use-case. Given its capabilities, we believe that the tools created could be effective across a variety of other fields.
The below video was presented to Senior stakeholders and Clients across multiple industries to explain the technology and approach.