title: Statistical detection of systematic election irregularities.
abstract: Democratic societies are built around the principle of free and fair elections, and that each citizen's vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons.
authors.affiliation: Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria.
authors.forename: Peter
authors.initials: P
authors.lastname: Klimek
authors.forename: Yuri
authors.initials: Y
authors.lastname: Yegorov
authors.forename: Rudolf
authors.initials: R
authors.lastname: Hanel
authors.forename: Stefan
authors.initials: S
authors.lastname: Thurner
mesh_terms: D000465:Algorithms; D002755:Choice Behavior; D002961:Civil Rights / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D011057:Politics; D011639:Public Opinion; D011640:Public Policy; D015203:Reproducibility of Results