Complexity scientists Peter Klimek (Complexity Science Hub Vienna) and Stefan Thurner (Complexity Science Hub Vienna, Santa Fe Institute) have developed an easy-to-use and cheap toolkit to detect election fraud and voter rigging. It works by detecting statistical irregularities in the data from posted election results.

“Our method is fast, cheap, and easy to use,” explains Klimek. “The only input we need is the election results.” Usually, these lists are provided online within hours after an election. “Our tests display a very specific pattern: the fingerprint of the poll,” Klimek points out. These fingerprints show places where manipulation can be excluded or hotspots where it occurred with high probability.

Their method, which was intially published in PNAS in 2012, has been applied to real-world elections such as the Turkish referendum and elections in 2017 and 2018, where the team did detect traces of fraud. 

While the scientists do not plan to run their method on the 2020 U.S. presidential election data — being all- absorbed in research related to the pandemic— Klimek and Thurner are happy to talk about the possibilities and advantages to using their method for an independent election monitoring effort.

For more information about the method, visit: