20.500.12556/RUP-22568 Designing the ideal political identity questionnaire using machine learning and ideology scales Political ideology shapes beliefs, behavior and attitudes toward society. Many existing questionnaires for measuring ideology are lengthy, repetitive, and misaligned with self-perception. This paper investigates whether a shorter, reliable, two-dimensional political identity questionnaire can be created using machine learning and psychometric methods. Sixty participants completed four ideological instruments (MFQ, SDO, RWA and 8values). Lasso regression and Random Forest with nested cross-validation identified predictive items, while psychometric evaluation included CFA and Cronbach’s alpha. Random Forest outperformed Lasso. Internal reliability was excellent and factor loadings supported a two-factor structure despite moderate model it. Findings show that ideology can be measured efficiently with reduced items, supporting applications in research, digital platforms and political psychology. political ideology questionnaire design machine learning psychometrics politična ideologija oblikovanje vprašalnikov strojno učenje psihometrija true false false University of Primorska Press Angleški jezik Slovenski jezik Neznano 2026-01-30 09:19:15 2026-01-30 09:19:17 2026-02-01 03:03:30 0000-00-00 00:00:00 2025 0 Koper 0 Str. 118-130 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.8 266380291 266572035 ZUP_Nikolic_Ana_2025.pdf ZUP_Nikolic_Ana_2025.pdf 1 B2A0169983B65A46E19DA8F151B8C321 a5e6da8c0f2366a59223317a93d70ede523ab5ca3fb05b28975911ae3d50dd92 c32f356b-fdb4-11f0-b092-005056ac49c0 https://repozitorij.upr.si/Dokument.php?lang=slv&id=32829 Založba Univerze na Primorskem 0 0 0