  Political campaigns are full of political ads posted by candidates on social
media. Political advertisements constitute a basic form of campaigning,
subjected to various social requirements. We present the first publicly open
dataset for detecting specific text chunks and categories of political
advertising in the Polish language. It contains 1,705 human-annotated tweets
tagged with nine categories, which constitute campaigning under Polish
electoral law. We achieved a 0.65 inter-annotator agreement (Cohen's kappa
score). An additional annotator resolved the mismatches between the first two
annotators improving the consistency and complexity of the annotation process.
We used the newly created dataset to train a well established neural tagger
(achieving a 70% percent points F1 score). We also present a possible direction
of use cases for such datasets and models with an initial analysis of the
Polish 2020 Presidential Elections on Twitter.
