Wednesday, July 18, 2012

60 Steps Revisited: Step 25 - Pay Attention To Daily And Weekly Rhythms

Back in 2009, I did a series of posts covering the excellent book Crime Analysis For Problem Solvers. The book is published by the US DOJ's Problem Oriented Policing Center (POP Center). Because of the value I think this book has for crime analysts, and policing in general, I am going to re-post this series on here on the blog.

We're up to Step 25 - Pay Attention To Daily And Weekly Rhythms in our walk through Crime Analysis For Problem Solvers. There is an old adage that "everything in life is cyclical". This is true not only in the change of seasons, but also in crime problems. Many crime problems revolve around the cyclical patterns of the lives of both offenders and their victims.

In the jurisdiction where I work, we often see the frequency of certain types of incidents increase in cyclical patterns. For instance, disturbances involving juveniles will increase immediately after the end of the school day when unsupervised children begin their journey home. Large public disturbances or fights in the parking lots of night clubs usually occur around closing time for the bars. Traffic accidents are more common during the morning and afternoon commutes.

The cyclical nature of these types of events make them relatively easy to predict and deploy solutions to combat them. In the example above involving errant school children, my agency increased staffing by detailing extra officers in the neighborhood near the school during the time these teens were making their way home. These officers were then able to respond to these incidents and take action rather then responding from other areas of town.

The authors state that there are three forms of temporal clustering.

  1. Diffused - Events relatively evenly spread over the entire day
  2. Focused - Events clustered around rush hours
  3. Acute - Events tightly packed within small periods
The authors state:
Focused and acute patterns immediately suggest temporal cycles that should be investigated.
Conducting temporal analysis of problems will often reveal such patterns. Most spreadsheet applications can create some very nifty charts that will help you to easily identify temporal patterns. The authors suggest performing an analysis of both time of day and day of week together rather than separately. The reason for this is that it is not unusual that if the frequency of events is calculated separately and then the results are combined you will end up with a misleading analysis. A surface or contour chart is a neat way to graph two variables together and determine the day/time that has the most events clustered around it.

Next time we'll look at Step 26 - Take Account of Long Term Change.

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