A Department of Homeland Security Emeritus Center of Excellence led by the University of Maryland

A consortium of researchers dedicated to improving the understanding of the human causes and consequences of terrorism

START researchers inform interns on “Machine Learning and Big Data for Predictive Modeling of Asymmetric Threats” (Photo Gallery)


START researchers inform interns on “Machine Learning and Big Data for Predictive Modeling of Asymmetric Threats” (Photo Gallery)

March 26, 2019Alexa Cottman-Robinson

On Tuesday, March 26, START’s Rachel Gabriel and Dr. Barnett Koven discussed how identifying social media trends and influencers could lend important insights for countering online radicalization. This talk was based on several previous and ongoing START projects about using trend forecasting and big data analytics to improve understanding and predictive capabilities regarding threats.

Barnett Koven and Rachel Gabriel deliver a lecture at START
START Researchers Barnett Koven and Rachel Gabriel discuss the possibilities of social media data collection. 

Students participate in a discussion at START
START interns raise their hands to indicate an interest in social media platforms. 

Barnett Koven delives a lecture to START students
Dr. Barnett Koven gives a lecture on machine learning to interns. 

 

Keywords

Investigators: 
Barnett S. Koven
Topics: 
Innovation and Technology Threat Assessment
Research Area: 
Counterterrorism