Artificial intelligence in political analysis: new horizons, opportunities, and challenges
DOI:
https://doi.org/10.24917/20845456.21.3Keywords:
artificial intelligence, data analysis, elections, electoral turnout, political preferencesAbstract
The application of artificial intelligence (AI) techniques is increasingly becoming a crucial component of scientific research, driven by greater computational power and the availability of high-quality data. AI enables precise forecasting, advanced multi-class classification, and the analysis of similarities across feature sets with varying dimensions that characterize individual data observations. This study employs exploratory data analysis and unsupervised machine learning methods to spatially examine electoral preferences in Poland from 2019 to 2024. The analysis is based on data from parliamentary, local government, and European Parliament elections. High voter turnout was observed in Cluster 4, which encompasses major metropolitan regions and central Poland, while areas with lower turnout were primarily located in eastern and northwestern Poland. Furthermore, the study reveals an intriguing relationship between voter turnout levels and support for specific political groups across two consecutive electoral cycles. Ethical considerations surrounding the application of AI in research on democratic processes were also explored, along with a discussion of future directions and related challenges.
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