Laila Wahedi
Core Data Science, Facebook
Nov 9, 2021
11:30 am
Nov 9, 2021
11:30 am
In-person
4 Thomas More St
London E1W 1YW, UK
London E1W 1YW, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Portland, ME 04101
Network Science Institute
2nd floor
2nd floor
Network Science Institute
11th floor
11th floor
177 Huntington Ave
Boston, MA 02115
Boston, MA 02115
Network Science Institute
2nd floor
2nd floor
Room
58 St Katharine's Way
London E1W 1LP, UK
London E1W 1LP, UK
Talk recording
This talk is hosted by the Social Design Lab. Register here.
Facebook has billions of active users, mostly going about their lives using the platform in positive ways. A small number of abusive actors spread misinformation, conspiracies, harassment, and hate. But harm can’t happen in isolation: in order for adversarial behavior to result in harm, it has to effect others, and as a result, concentrates and spreads through networks. In this talk, we’ll discuss some of the methods we’ve developed to identify harmful networks in all that noise, and how that detection work can help us inform partner enforcement teams to make the platform safer.
About the speaker
Laila A. Wahedi is a research scientist in the Computational Social Science team within Core Data Science at Facebook. She is also affiliated with the Massive Data Institute at the McCourt School of Public Policy at Georgetown University. Her research interests vary across the field of security studies and international relations, but focus on understanding networks of militant organizations: why do groups align, and what is the impact of patterns of alignment on these groups?
Laila has also worked in strategic force mix and readiness issues with the Institute for Defense Analyses. She has done work on assessing force mixes and readiness requirements for an uncertain future, understanding and modeling force generation across the military services, and on the impact of energy on force readiness across the services. Laila enjoys taking on side projects in her spare time. Her interests include computational modeling, and understanding the neural mechanisms driving competition and cooperation.
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