Magazine article American Scientist

First Person: Andrea L. Bertozzi and P. Jeffrey Brantingham

Magazine article American Scientist

First Person: Andrea L. Bertozzi and P. Jeffrey Brantingham

Article excerpt

What types of crimes do you model?

Bertozzi: We're using statistical methods, and these methods work verywell when you have a large population where you've got a number of different interacting players in the process: for example, residential burglaries, criminals interacting with the environment. Then we look at how one event might trigger another event. To date, we've mainly focused on crimes of opportunity and ones that happen fairly frequently.

Brantingham: It depends on the timescale. If you want to predict crimes on timescales of minutes to hours to maybe even days, you need very large populations. If you're talking about events like the shootings that happened in Orlando or at UCLA, it's potentially possible to predict how many events like that are going to occur over the course of a year or maybe two years or five years, but not on a very short timescale of hours to days.

Is human behavior a factor?

Bertozzi: We're not tailing criminals and looking at how the criminals are making decisions. Rather, we're looking at actual patterns of events themselves and the location of the events. For example, if you have a house that's broken into, what happens in the general vicinity of that house? Does the probability of another break-in change at neighboring houses? It turns out that you can quantify those things very carefully. We're much less focused on the individuals committing the crime than we are on the spatial targets of the crime.

Brantingham: In many cases, what's driving where and when crime occurs is less dependent upon the motives of the offender than on the structure of the opportunities. That's why we can focus in on the events themselves rather than on the perpetrator and gain a lot of traction predicting where and when those crimes will occur.

Do other types of modeling relate to this problem?

Bertozzi: We looked at some models of microorganisms that change the environment around them and make it more hospitable, which causes aggregations to form. We also tapped into models related to earthquakes and their triggered aftershocks, which turn out to be wonderful statistical models for human activity.

What amount of data do you work with?

Brantingham: It depends on the timescale, but if you're looking at doing crime prediction on the order of days to x maybe weeks within a | particular region, you f can gain some trac| | with hundreds I of events. Most police g departments, even rel> > small ones, can find hundreds of events in their jurisdictions and start to use these models for prediction purposes.

What time frame and types of data do you use to build the model?

Brantingham: Typically, we look at years' worth of data in the background for predicting crime today. The process is an evolving one, not unlike Netflix. They have your entire movie-watching history in the background, and the movie you watch today changes the way the model appreciates how your tastes are evolving. In the same way we have lots of crime data going back years in the background, and the events that occur today change how we view the likelihood of crime occurring tomorrow.

The only data that we've really worked with over the long term is strictly the minimum of what you need to classify an event: We talk about what type of crime this is, a classification provided by the police department, where did it occur, and when did it occur-just those three things. You might say to yourself, "Well, what about street networks, and what about weather patterns, and what about demographic characteristics?" A lot of that stuff that we want to believe is really important for understanding crime actually is not nearly as important as we think it is. It's very difficult to figure out how do we actually use information about poverty or socioeconomic status as a component of models to forecast crime.

All of that additional information is already built into the events themselves. You can think of it as the event having already distilled all of those other variables in driving where and when it occurs. …

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