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Using Engineering Techniques To Improve Data On Gun Violence

After the 2007 mass shooting at Virginia Tech, Maurizio Porfiri of New York University, who received his Ph.D. at the Virginia school, found that the data and evidence in gun violence research mostly didn't utilize robust mathematical equations. Porfiri decided to "see if we could use engineering techniques to bring insight into gun violence to help policymakers make good decisions informed by scientific evidence." In 2020, the Italian native became the first researcher to receive a $2 million grant from the National Science Foundation earmarked specifically for gun-related research. This week he published research on how "fame-seeking" mass shooters choose their locations. He has also researched why gun owners purchase firearms after a mass shooting and statistical models for predicting monthly U.S. gun homicides, reports CBS News.

Porfiri says, "In gun violence, the level of engineering sophistication is not the same as that you find in other public health areas. I've seen gun violence research that takes different approaches but there are few mathematical approaches that are robust enough to take nuances into consideration." He notes that data on guns from the Centers for Disease Control "has a very, very big delay. Typically a policymaker receives correct information between one to two years after the incident ... And things change very rapidly." He says he builds tools "that can sort through and understand many different pieces of information; including Twitter, background checks, and Google Trends. So policymakers don't have to wait two years. The data can tell you right away what's happening today, and what happened last year." He adds, "What we can do is provide scientifically backed information for policymakers to act. That we can do. We try to make all of our data open-source so everyone can use it — with some exceptions. We don't publish the mass shooting database so as not to encourage more violence."


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