Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections

Lukasz Augustyniak, Krzysztof Rajda, Tomasz Kajdanowicz, Michał Bernaczyk


Abstract
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.
Anthology ID:
2020.winlp-1.28
Volume:
Proceedings of the The Fourth Widening Natural Language Processing Workshop
Month:
July
Year:
2020
Address:
Seattle, USA
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
110–114
Language:
URL:
https://aclanthology.org/2020.winlp-1.28
DOI:
10.18653/v1/2020.winlp-1.28
Bibkey:
Cite (ACL):
Lukasz Augustyniak, Krzysztof Rajda, Tomasz Kajdanowicz, and Michał Bernaczyk. 2020. Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections. In Proceedings of the The Fourth Widening Natural Language Processing Workshop, pages 110–114, Seattle, USA. Association for Computational Linguistics.
Cite (Informal):
Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections (Augustyniak et al., WiNLP 2020)
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Video:
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