1143 | 822 | Electoral Fraud Detections in Hungary with Spatial Big Data Methodologies

Fraudulent activities before and at the day of general elections are widely reported from Hungary as well as other post-socialist countries, although its systematic manner has never got proven. In collaboration with OSCE and local Hungarian civil organisations with extensive field experience, we determined the so-called “red flag” indicators of the more than 10 thousand precincts that suggest the mass movement of voters from their home address to the polling stations. _x000D_
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Prompt increase in local turnout during election day, disproportionately high number of void ballot papers, vote share of individual party candidate is higher than party list votes, are the typical such indicators that we can use for filtering and then to proceed with a more granular research in local context. The same research exercise has been conducted for general elections between 2010 and 2022 (4 consecutive elections) and a relatively large number of overlapping municipalities and city neighbourhoods with bad housing and living conditions could have been identified. _x000D_
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With this research, our goal is to provide a good practise of how applied electoral geography could be utilised in favour of securing a free and fair elections. Nevertheless we can also point out the most vulnerable social groups in terms of organised electoral manipulation attempts.

Matyas Bodi
Phd Candidate, ELTE Budapest, Dep. of Human and Economical Geography.

ID Abstract: 822