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This work is dedicated to finding the determinants of voting behavior inPoland at the poviat level. 2019 parliamentary election has been analyzed andan attempt to explain vote share for the winning party (Law and Justice) hasbeen made. Sentiment analysis of tweets in Polish (original) and English(machine-translations), collected in the period around the election, has beenapplied. Amid multiple machine learning approaches tested, the bestclassification accuracy has been achieved by Huggingface BERT onmachine-translated tweets. OLS regression, with sentiment of tweets andselected socio-economic features as independent variables, has been utilized toexplain Law and Justice vote share in poviats. Sentiment of tweets has beenfound to be a significant predictor, as stipulated by the literature of thefield.

Sentiment of tweets and socio-economic characteristics as the  determinants of voting behavior at the regional level. Case study of 2019  Polish parliamentary election