What are the drivers of violent extremism on-line? What do we know about its impact? How do we engage industry and leverage the potential of modern analytical techniques to create capabilities to monitor for “risk factors” while remaining consistent with important principles as the United Nations Universal Declaration of Human Rights? One option is to adopt the WHO public health surveillance model to tracking risk factors in on-line media. Doing so will require developing an OpenData standard for social media data for community security – and buy-in from major social media platforms to participate in such an effort.
Rafal Rohozinski is the CEO and Chief Innovation Officer at SecDev Group and co-founder of the Secdev Foundation. He is also a senior fellow for Future Conflict and CyberSecurity at the London-based International Institute for Strategic Studies. These remarks were delivered at a special meeting of meeting of the United Nations Counter Terrorism Committee, UN Security Council, 1 December 2016, and draw upon a recent Secdev/UNDP study of terrorist use of social media in Bangladesh.
On March 6th the CIC National Capital Branch, in cooperation with the SecDev Foundation, hosted the event, Women, Violent Extremism and the Internet: Empowering Prevention; Dealing with Risk.
This summary captures the main findings of a longitudinal content analysis of a known foreign fighter’s (FF) public social media activity for signs of radicalization toward violent extremism.
This experiment used the Twitter profile of a U.K. national, verified to be an active foreign fighter (FF) in the Syrian civil war, as the seed for constructing a network topology based on social media interactions.
This research note summarizes experimental research conducted by The SecDev Group in 2013, as part of a Public Safety Canada, Kanishka-funded project looking at social media analytics and the prevention of violent extremism.
In 2013, The SecDev Group undertook a 10-month Kanishka-funded project that set out, in part, to explore methodologies and technologies for open source social media (OSSM) research and their potential utility for detecting weak signals of radicalization towards violent extremism online.