Trends and Outliers

Can Analytics Fight Crime?

It’s doubtful the next crime fighting cartoon hero will be “Analytics Man,” but analytics can be a tool in the arsenal of crime fighters.A blog focusing on college campus crime recently reported on a project to analyze campus crime using Spotfire.  This project was done by Hyoungtae Cho and Bo Lui, graduate students in Computer Science at University Maryland, College Park.  The students wondered if they could use analytics to identify crime hot spots, peak hours, and maybe even prevent crime.

The project used data publicly released by the Department of Public Safety at University Maryland, College Park and the students culled out irrelevant data (such as traffic stops) to come to a core data set of 4849 cases in 13 categories of crimes.  The analytics looked at various factors, such as crime type, location, time and report time.

Using Spotfire for analytics, the project concluded:

• Property destruction is increasing.  Analytics showed the overall number of occurrences fluctuates, but the number of incidents is steadily increasing.  No underlying explanation was identified.
• October is the most unsafe month on campus.  Campus populations fluctuate greatly during the year.  Drilling down, the analytics showed October has the highest rates for larceny, property destruction and assault.  The analytics actually generated a finding contradictory to the common thought that crimes spiked at the beginning of the school year (September).
• There are specific “unsafe” zones on campus.  Spotfire enabled the students to create a visual tree map of crime, with different sizes and colors displaying crime counts.  The analytics led to an intriguing conclusion: top crime locations were dynamic, high activity buildings, but ones in which people often left their property unattended.
• A building housing several social science departments had the highest rate of burglary.  The students used the same tree map visualization method to analyze location data and burglary rates.
• 3pm – 5pm is the peak time for crimes.  Spotfire analytics enabled the students to plot crime incidents according to the time of day they occurred.  In addition to revealing the general peak time for crime, the analysis also showed that 4pm – 6pm was the peak time for burglary.

If knowledge is the most powerful tool in a crime fighter’s arsenal, analytics can play a significant role in crime fighting. 

 Kelley Kassa
Spotfire Blogging Team

Image Credit: Microsoft Office Clip Art

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