  Every day, the world is flooded by millions of messages and statements posted
on Twitter or Facebook. Social media platforms try to protect users' personal
data, but there still is a real risk of misuse, including elections
manipulation. Did you know, that only 13 posts addressing important or
controversial topics for society are enough to predict one's political
affiliation with a 0.85 F1-score? To examine this phenomenon, we created a
novel universal method of semi-automated political leaning discovery. It relies
on a heuristical data annotation procedure, which was evaluated to achieve 0.95
agreement with human annotators (counted as an accuracy metric). We also
present POLiTweets - the first publicly open Polish dataset for political
affiliation discovery in a multi-party setup, consisting of over 147k tweets
from almost 10k Polish-writing users annotated heuristically and almost 40k
tweets from 166 users annotated manually as a test set. We used our data to
study the aspects of domain shift in the context of topics and the type of
content writers - ordinary citizens vs. professional politicians.
