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Finding the statistical fingerprints of election thieves

Date:
September 25, 2012
Source:
Santa Fe Institute
Summary:
Scientists examined voter data from a dozen recent elections around the world and found statistical evidence for election fraud in two of them.

In fair elections, a nation's voting pattern tends to feature one cluster, showing a general trend of voter turnout and vote for the victorious party (though some nations' regional voter preferences can distort it). Rigged ones show a cluster, but with a smear of votes toward the upper right for incremental fraud. Extreme fraud has a second, smaller, completely separate cluster at the top right corner, signifying up to 100 percent turnout and votes for the winner.
Credit: Image courtesy of Santa Fe Institute

The art of swaying an election is as old as democracy itself. Strategies like ballot stuffing, redistricting, voter venue switching, and temporary traffic detours have skewed regional results, and sometimes determined the winner.

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While some tactics get exposed the old fashioned way -- by angry voters or investigations -- others don't. But new research suggests some kinds of election fraud leave a trace in the voting data.

In a paper appearing September 24 in Proceedings of the National Academy of Sciences, a team led by Stefan Thurner brought science to the problem.

"We got into this by chance, when a Russian colleague brought us the 2011 Russian Duma-election data and asked us to take a look," says Thurner. "From the first look we were all pretty shocked, and decided to take a second look."

Thurner, a Santa Fe Institute External Professor who heads the Section for Complex Systems at the Medical University of Vienna, and colleagues looked for two kinds of rigging: incremental fraud, where votes for one party are kept in the ballot box while those for the other candidates are tossed, and extreme fraud, which shows 100 percent voter turnout in a district, all voting for the same party.

The team examined data on number of eligible voters, valid votes, and votes for the winning candidate (or party) from a dozen recent elections around the world. By comparing the distributions of votes for the winning candidate against turnout numbers, they found that rigged elections show a different voting pattern than fair ones.

In fair elections, a nation's voting pattern tends to feature one cluster, showing a general trend of voter turnout and vote for the victorious party (though some nations' regional voter preferences can distort it). Rigged ones show a cluster, but with a smear of votes toward the upper right for incremental fraud. Extreme fraud has a second, smaller, completely separate cluster at the top right corner, signifying up to 100 percent turnout and votes for the winner.

Next, the team developed a model to detect how much forged or manipulated results affected the outcome, then ran through all possibilities of both fraud types playing 0 percent to 100 percent of a part in the election, and compared those to actual data to determine their prevalence.

Among the countries studied, data from recent elections in Russia and Uganda showed both the smear of incremental fraud and the second cluster of extreme fraud, with up to 64 percent of districts being affected in Russia's 2011 vote and 39 percent in 2012. Other countries' data showed little to no such trends.

"I think it could contribute to the benefit of democracy if for every nationwide election on this planet, the raw data is made available on say a United Nations or OECD database," says Thurner. "One could then think of a set of quality standards and checks for any election -- like the ones we presented -- or better ones."


Story Source:

The above story is based on materials provided by Santa Fe Institute. Note: Materials may be edited for content and length.


Journal Reference:

  1. P. Klimek, Y. Yegorov, R. Hanel, S. Thurner. Statistical detection of systematic election irregularities. Proceedings of the National Academy of Sciences, 2012; DOI: 10.1073/pnas.1210722109

Cite This Page:

Santa Fe Institute. "Finding the statistical fingerprints of election thieves." ScienceDaily. ScienceDaily, 25 September 2012. <www.sciencedaily.com/releases/2012/09/120925152137.htm>.
Santa Fe Institute. (2012, September 25). Finding the statistical fingerprints of election thieves. ScienceDaily. Retrieved November 26, 2014 from www.sciencedaily.com/releases/2012/09/120925152137.htm
Santa Fe Institute. "Finding the statistical fingerprints of election thieves." ScienceDaily. www.sciencedaily.com/releases/2012/09/120925152137.htm (accessed November 26, 2014).

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