From legal to technical concept: Towards an automated classification of German political Twitter postings as criminal offenses

Frederike Zufall, Tobias Horsmann, Torsten Zesch


Abstract
Advances in the automated detection of offensive Internet postings make this mechanism very attractive to social media companies, who are increasingly under pressure to monitor and action activity on their sites. However, these advances also have important implications as a threat to the fundamental right of free expression. In this article, we analyze which Twitter posts could actually be deemed offenses under German criminal law. German law follows the deductive method of the Roman law tradition based on abstract rules as opposed to the inductive reasoning in Anglo-American common law systems. This allows us to show how legal conclusions can be reached and implemented without relying on existing court decisions. We present a data annotation schema, consisting of a series of binary decisions, for determining whether a specific post would constitute a criminal offense. This schema serves as a step towards an inexpensive creation of a sufficient amount of data for an automated classification. We find that the majority of posts deemed offensive actually do not constitute a criminal offense and still contribute to public discourse. Furthermore, laymen can provide sufficiently reliable data to an expert reference but are, for instance, more lenient in the interpretation of what constitutes a disparaging statement.
Anthology ID:
N19-1135
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Jill Burstein, Christy Doran, Thamar Solorio
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1337–1347
Language:
URL:
https://aclanthology.org/N19-1135
DOI:
10.18653/v1/N19-1135
Bibkey:
Cite (ACL):
Frederike Zufall, Tobias Horsmann, and Torsten Zesch. 2019. From legal to technical concept: Towards an automated classification of German political Twitter postings as criminal offenses. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 1337–1347, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
From legal to technical concept: Towards an automated classification of German political Twitter postings as criminal offenses (Zufall et al., NAACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/N19-1135.pdf
Code
 Horsmann/NAACL-2019-legal