Penn State Research Team Uses Big Data to Explore Crime Rates
February 2, 2017
The article on E&T titled Social Media and Taxi Data Improve Crime Pattern Picture delves into a fascinating study that uses big data involving taxi routes and social media location labels from sites like Foursquare to discover a correlation between taxis, locations of interest, and crime. The study was executed by Penn State researchers who are looking for a more useful way to estimate crime rates rather than the traditional approach targeting demographics and geographic data only. The article explains,
The researchers say that the analysis of crime statistics that encompass population, poverty, disadvantage index and ethnic diversity can provide more accurate estimates of crime rates … the team’s approach likens taxi routes to internet hyperlinks, connecting different communities with each other… One surprising discovery is that the data suggests areas with nightclubs tend to experience lower crime rates – at least in Chicago. The explanation may be that it reflects people’s choices to be there.
This research will be especially useful to city planners interested in how certain spaces are being used, and whether people want to go to those spaces. But the researcher Jessie Li, an assistant professor of information sciences, explained that while the correlation is clear, the underlying cause is not yet known.
Chelsea Kerwin, February 2, 2017
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