Oath Keepers Leaked Incoming Emails State Frequency Map

https://www.theguardian.com/us-news/2021/oct/01/capitol-attack-oath-keepers-far-right-militia-group

The recent Oath Keepers leak had emails separated by state code (xx@oathkeepers.org). The frequency of emails sent from people to the various addresses can be obtained and converted to CSV with the following command from the MBOX file directory:

grep -E "^From" * | cut -d ':' -f1 | grep -E "^[a-z][a-z]$" | sort | uniq -c | sed -r "s/^[ ]+//g" | tr ' ' ',' > ok_state_freq.csv

These emails represent people attempting to sign up who vary in background, but also a few hate mails and a bunch of spam. The results are not very conclusive about anything other than which email addresses are most frequently used.

Load Data Into R

library(ggplot2)
library(mapproj)
library(fiftystater)
state_codes <- read.csv("shared/state_codes.csv")
ok_state_freq <- read.csv("ok_state_freq.csv", header=FALSE)
names(ok_state_freq) <- c("Frequency", "State.Code")
ok_state_freq <- merge(ok_state_freq, state_codes)

Mapping

g <- ggplot(ok_state_freq, aes(map_id=State.Name))
g <- g + ggtitle("Oath Keepers Leaked Incoming Email Frequency by State")
g <- g + geom_map(aes(fill=Frequency), map=fifty_states)
g <- g + expand_limits(x=fifty_states$long, y=fifty_states$lat)
g <- g + xlab("") + ylab("") + theme(panel.background=element_blank())
g <- g + scale_x_continuous(breaks=NULL) + scale_y_continuous(breaks=NULL)
g <- g + scale_fill_continuous(low="#300000", high="#E00000", guide="colorbar")
g

plot of chunk unnamed-chunk-1