The idea is that different sets of people have different likelihoods of being in one of these terrible shootings, depending on your geographical location. But there's a sort of even more fine grained data about who your friends are that could be used to really say, no, you in particular, are at heightendresk right? So how do you go from these structural conditions, which are real, which create these networks, to trying to figure out who's in harm's way to day? And that's the jump take,. You want to create small networks with a lot of guns.
The United States is suffering from an epidemic of tragic gun violence. While a political debate rages around the topic of gun control, it remains important to understand the causes and possible remedies for gun violence within the current system. Andrew Papachristos is a sociologist who uses applied network science to study patterns of street violence in urban areas. His research shows that such violence is highly non-random; knowing something about the social networks of perpetrators and victims can help identify who might be at heightened risk of gun violence. It’s an interesting example of applying ideas from mathematics and computer science to real-world social situations.
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Andrew Papachristos received his Ph.D. in sociology from the University of Chicago. He is currently a professor of sociology at Northwestern University, and a faculty fellow at the Institute for Policy Research. He is also founding director of the Northwestern Neighborhoods and Networks Initiative.
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