Back in the 90s, pagers were a common form of mobile communication in the US. To send a message to a pager, you could call a special phone number, say your message, and the text of the message would appear in the screen of the pager.
Wikileaks hacked their way into the data produced by pagers around the terrorist attacks of 9/11 in 2001. They released all data publicly on this website. This data was analyzed to measure the emotional response of americans to the terrorist attacks. Previous works on emotions after 9/11 are among the first cases of the analysis of emotions in social media data, in particular the analysis of blogs by Cohn, Mehl, and Pennebaker.
The original analysis of pager data by Back, Küfner, and Egloff used the LIWC method to measure the frequency of use of words expressing sadness, anxiety, and anger. They calculated the mean percentage of words in each class over windows of 30 minutes. The figure on the right shows the result, a steady increase of anger term frequency. Quoting the article itself:
“We were able to determine that people did not react primarily with sadness; that they experienced a number of anxiety outbursts, but recovered quickly; and that they steadily became angrier.”
Cynthia Pury inspected the results and found a repeating pattern in the Wikileaks data. Out of the 16,624 instances of anger words 5,974 (35.9%) were in nearly identical messages:
These messages all looked like this:
“Reboot NT machine [name] in cabinet [name] at [location]:CRITICAL:[date and time].”
The word “critical” is contained in the anger word list of LIWC and thus it was being counted in each of these messages. These were automated error messages sent by servers to system administrators, probably from systems that were affected by the infrastructure damage of 9/11. A reanalysis of the data removing these messages leaves a result like this: