Inside Serial Killer Data: Part Two

serial_data

Tags:

This is the second part of a two-part series on serial killer data. To read part one and to learn more about the origins of this data, check out part one here.

One of the best things about this dataset is that it includes detailed information on the victims and not just the killers. The data categorizes victims under labels such as prostitutes, employees, or spouses. The categorization features both general and specific labels. For example a victim could be labeled as “home invasion” and their specific label could be something like “home invasion, elderly woman”.

The following charts show the top ten most common “general” and “specific” victim types.

Inside Serial Killer Data: Part Two

Inside Serial Killer Data: Part Two

Before we get into the analysis, let me clarify a few things. “General public” is one size fits all term for pedestrians and other people who don’t have a clearly defined relationship with the killer. It also encompasses very specific identifiers such as “hikers” or “party-goer”. “Street People” refers to people such as the homeless, prostitutes, junkies, and more. “Employees” basically means any victim from a workplace or interacts with a killer in a service capacity. This includes customers, cab drivers, judges, or job applicants.

“General Public” and women have a significant presence in these two graphics. The popularity of “General Public” indicates that the most popular type of victims for killers are ones are who do not know their killers. Switch to the specific graph, you’ll see that half of the spots fall under “General Public”.”Family” at the three position is interesting to me because when you think of a stereotype of a serial killer, you don’t automatically imagine them killing family members.

In the specific graph “General Public Women” claims the top spot by more than 100 and in second is “Prostitute” a victim category that is overwhelmingly female. “Spouse” which is majority female comes in at number four while “Home Invasion Women” is at number seven.

In the last article, one of the major discoveries was that there are basically three motivations for killers: anger, financial, and enjoyment. We were able to deduce that there are significant differences amongst killers with those motives. Now let’s find the differences in victims of killers with those motives.

The following three charts display the top five most common type of victims for each of the three motives mentioned earlier.

Inside Serial Killer Data: Part Two Inside Serial Killer Data: Part Two Inside Serial Killer Data: Part Two

Takeaways:

  • “Prostitute” only shows up in the enjoyment chart and not in others, suggesting that when killers target prostitutes they do so for pleasure.
  • “Spouse” appears in the anger and financial charts but not in enjoyment. If a killer murders their spouse its more likely they do it for money or out of rage but not it’s likely they’ll do it for the thrill.
  • “General Public” is the most popular label in the anger and enjoyment graphics but is number three in financial. This makes sense because if you’re murdering someone whom you don’t or barely know, it’s not likely you’re doing it for the money.
  • “Home Invasion” is present in enjoyment and financial but not in anger, I guess it’s not common for serial killers to go around breaking into people’s homes out of rage.
  • “Hospital Patients” only appears in enjoyment, “Employees” only appears in financial, while every label in anger also shows up either of the other two charts.

This exercise has been incredibly fun and illuminating. The great power is data is its ability to better understand and to bring nuance to a certain subject and that was very evident in this project. The data proved that actual serial killers don’t entirely live up to the caricatures seen in movies and that they are a diverse population that require different lenses through which to analyze them.

A big thanks again to Enzo Yaksic and Professor Mike Aamodt for their work on this issue and for sharing their data with ODSC.


©ODSC 2016

Latest Posts

dask_release
Dask Release 0.13.0

01/18/2017

Related posts