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