The Star Tribune recently ran an article about a new study from George Washington University tracking cases of Americans who traveled to join jihadist groups in Syria and Iraq since 2011. The print version of the article was accompanied by a graph showing that Minnesota has the highest rate of cases in the study. TSP editor Chris Uggen tweeted the graph, noting that this rate represented a whopping seven cases in the last six years.

Here is the original data from the study next to the graph that the paper published:

(Click to Enlarge)

Social scientists often focus on rates when reporting events, because it make cases easier to compare. If one county has 300 cases of the flu, and another has 30,000, you wouldn’t panic about an epidemic in the second county if it had a city with many more people. But relying on rates to describe extremely rare cases can be misleading. 

For example, the data show this graph misses some key information. California and Texas had more individual cases than Minnesota, but their large populations hide this difference in the rates. Sorting by rates here makes Minnesota look a lot worse than other states, while the number of cases is not dramatically different. 

As far as I can tell, this chart only appeared in the print newspaper photographed above and not on the online story. If so, this chart only went to print audiences. Today we hear a lot of concern about the impact of “filter bubbles,” especially online, and the spread of misleading information. What concerns me most about this graph is how it shows the potential impact of offline filter bubbles in local communities, too.

Evan Stewart is an assistant professor of sociology at University of Massachusetts Boston. You can follow his work at his website, or on BlueSky.