Predicting perceived ethnicity with data on personal names in Russia

Abstract In this paper, we develop a machine learning classifier that predicts perceived ethnicity from data on personal names for major ethnic groups populating Russia. We collect VK, the largest Russian social media website. Ethnicity was coded languages spoken by users and their geographical location, with manually cleaned crowd workers. The shows accuracy of 0.82 scheme 24 0.92 15 aggregated groups. It can be used research relations in Russia, sets have but not ethnicity.