Aesthetics > Function?: An Infographic Analysis

The infographic, "Who Is Most Likely To Murder You?" posted on Instagram by Mona Chalabi illustrates data from the US Bureau of Justice Statistics 2021. It presents comparative statistics on female and male victims over five different victim-offender relationship categories in an artistic and visually grabbing way.  But do the added visual elements enhance clarity, or do they distract from the data's real message? 

Mona Chalabi's Infographic "Who Is Most Likely to Murder You?"

The first strength comes from the unexpected graphics that strike readers. Through coffin imagery of the murder rates of female and male victims across different victim-offender relationships, viewers are left with little choice but to explore the information further. Moreover, the bar chart organization is seemingly easy for readers understand.  The labels along the top of the chart clearly identify a comparison of female to male victims, and the contrasting yellow and purple colors further differentiating the two categories.  

Regardless of these strengths, the aesthetic choices also produce several drawbacks.  Though the use of colors can be beneficial, the use of TOO much color can become counterproductive. The infographic's use of four different colors, (pink, brown, yellow, blue), distract the viewer and take away from the key points of focus.  The bold yellow and purple draw your attention away from the brown, which represents the most crucial data.  Simplifying the infographic to include just one or two colors would more concisely highlight the distinct dataset for men and women. 

The infographic's weakest area is, however, the X-axis.  Upon deeper inspection of the chart, the X-axis is misleading in a number of ways.  Firstly, the columns for Female Victims and Male Victims are directly joined side by side, reading as a singular chart with one continuous X-axis.  This creates confusion for viewers under the assumption that both genders share the same 0% starting point at the axis intersection. In actuality, the second baseline for the dataset on Male Victims is located in the middle of the "shared" X-axis, and in place of what should be the 40% under Female Victims. Additionally, if Mona Chalabi was going to organize the statistics more by gender categories, they should have also expanded the percentiles along the X-axis up to 100%.  This would give viewers a more honest visual of the percentage of murder victims by relationship category; and thus prevent issues of data (ie. Male Victim by "Friend or other known person") reading like 100% instead of 40%.  

In revising this infographic, I would keep the bar chart format but tweak it so the victim genders were not split into their own columns.  Instead, the data from both genders would be paired within each Victim-offender relationship category. 

Example of how you could show Female and Male data within each category as referred to above. 
 

Although I cant deny that Mona Chalabi's infographic is intriguing with it's colors and illustrations, it ultimately failed at an infographic's main job of provide the information clearly and concisely.  So, in this analysis of "Who Is Most Likely To Murder You?" the aesthetics were taken too far and were the downfall of the infographic's functionality.