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Forensic analysis of the Turkey 2023 presidential election reveals extreme vote swings in remote areas

Concerns about the integrity of Turkey’s elections have increased with the recent transition from a parliamentary democracy to an executive presidency under Recep Tayyip Erdoğan.

Election forensics tools are used to identify statistical traces of certain types of electoral fraud, providing important information about the integrity and validity of democratic elections. Such analyses of the 2017 and 2018 Turkish elections revealed that malpractices such as ballot stuffing or voter manipulation may indeed have played a significant role in determining the election results.

Here, we apply election forensic statistical tests for ballot stuffing and voter manipulation to the results of the 2023 presidential election in Turkey. We find that both rounds of the 2023 presidential election exhibit similar statistical irregularities to those observed in the 2018 presidential election, however the magnitude of these distortions has decreased. We estimate that 2.4% (SD 1.9%) and 1.9% (SD 1.7%) of electoral units may have been affected by ballot stuffing practices in favour of Erdoğan in the first and second rounds, respectively, compared to 8.5% (SD 3.9%) in 2018. Areas with smaller polling stations and fewer ballot boxes had significantly inflated votes and turnout, again, in favor of Erdoğan. Furthermore, electoral districts with two or fewer ballot boxes were more likely to show large swings in vote shares in favour of Erdoğan from the first to the second round.

Based on a statistical model, it is estimated that these shifts account for 342,000 additional ballots (SD 4,900) or 0.64% for Erdoğan, which is lower than the 4.36% margin by which Erdoğan was victorious. Our results suggest that Turkish elections continue to be riddled with statistical irregularities, that may be indicative of electoral fraud.

P. Klimek, A. Aykac, S. Thurner, Forensic analysis of the Turkey 2023 presidential election reveals extreme vote swings in remote areas, PLoS ONE 18(11) (2023) e0293239.

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