Denver Hate Crime Mapping: Visualizing Fluctuations through Linear Programming

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Denver Hate Crime Mapping: Visualizing Fluctuations through Linear Programming
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Auraria Library Data to Policy Fall 2018
Gatliffe, Kathleen
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Bias-motivated crime--criminal acts galvanized by prejudice-- are of special interest to the Federal Bureau of Investigation and thus many police departments, including Denver, collect information on such crimes monthly and share their data with the national database. In this project, linear optimization techniques were applied to the bias-motivated crime database maintained by the Denver Police Department. This research detected patterns of interest, some matching national trends and others in opposition.
Collected for Auraria Institutional Repository by the Self-Submittal tool. Submitted by Kathleen Gatliffe.
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! Kathleen Gatli e Mathematical and Statistical Sciences, University of Colorado Denver " Denver Hate Crime Mapping Visualizing Fluctuations Through Linear Programming" For Further Information Please contact Kathleen Gatliffe: kathleen.e.gatli Bias Motivated Crime Crime committed against a person or persons in an attempt to victimize an entire group of people Commonly called hate crime. In Colorado, protected categories include: disability, ethnicity, gender identity, race, religion, and sexual orientation. The Denver Police Department takes part in the national hate crimes database National statistics compiled monthly by the FBI as part of the Uniform Crime Reporting (UCR) program and released in a yearly report Reported Hate Crimes 2010-2017 Case Study 2011-2014 Case Study 2014-2017 Linear Programming: Techniques for finding the optimal solution to sets of linear equations Assignment Problem: A class of linear program that can be used to show shifts over time, such as the location of hate crimes in Denver Let i denote the crimes in the earlier year, and j be the crimes in the following year, then Percentage Reported Hate Crimes in Denver by Social Bias Type Primary References" Reported hate crimes in Denver tend to follow national trends, but due to the relatively small number of reported crimes, fluctuations can appear magnified The percentage makeup of bias motivated crime in Denver tends to be much lower than the national average for crimes against race and religion Denver tends to report a higher percentage of crimes related to sexual orientation than the national average Since 2010, crimes related to ethnicity have increased in Denver, exceeding the national average Denver has seen a dramatic increase in crimes related to gender identity in 2016-17 0 2000 4000 6000 8000 10000 2010 2011 2012 2013 2014 2015 2016 2017 0 20 40 60 80 2010 2011 2012 2013 2014 2015 2016 2017 Letting the Euclidean distance between locations be c ij ; our objective function minimizes the summation of all distances Our constraints are then that the assignments from each origin equal one, NATIONAL" DENVER For all And that the assignments to each destination are equal to the ratio between the number of origins and destinations For all Yellow dots depict reported crimes 2011 and orange dots depict crimes in 2014. Bias motivated crime was high at the beginning of the decade but declined over the next several years Reported hate crimes were scattered throughout the city in 2011, often occurring near major roadways In 2014, we see hate crime condensing into downtown with isolated incidents in less travelled areas Hate crimes in Five Points and North Capitol Hill moved onto side streets in 2014 Yellow dots depict reported crimes in 2014 and orange dots depict crimes in 2017. In 2016-2017 reported hate crimes increased across the city New hot spots developed in 2017, including Hampden and the neighborhoods near Ruby Hill Denver University is a hot spot with numerous reports of anti-Jewish activities Hate crimes remain in Downtown but now center on Union Station and Arapahoe The increase in 2017 seems to be primarily driven by increased reports of criminal mischief / opendata /hate-crime Luenberger D.G. and Ye, Y. 1973. Linear and Nonlinear Programming Springer. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2010 2011 2012 2013 2014 2015 2016 2017 Race Sexual Orientation Religion Ethnicity Gender Identity Disability