Annotation and Detection of Arguments in Tweets

Robin Schaefer, Manfred Stede


Abstract
Notwithstanding the increasing role Twitter plays in modern political and social discourse, resources built for conducting argument mining on tweets remain limited. In this paper, we present a new corpus of German tweets annotated for argument components. To the best of our knowledge, this is the first corpus containing not only annotated full tweets but also argumentative spans within tweets. We further report first promising results using supervised classification (F1: 0.82) and sequence labeling (F1: 0.72) approaches.
Anthology ID:
2020.argmining-1.6
Volume:
Proceedings of the 7th Workshop on Argument Mining
Month:
December
Year:
2020
Address:
Online
Venue:
ArgMining
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
53–58
Language:
URL:
https://aclanthology.org/2020.argmining-1.6
DOI:
Bibkey:
Cite (ACL):
Robin Schaefer and Manfred Stede. 2020. Annotation and Detection of Arguments in Tweets. In Proceedings of the 7th Workshop on Argument Mining, pages 53–58, Online. Association for Computational Linguistics.
Cite (Informal):
Annotation and Detection of Arguments in Tweets (Schaefer & Stede, ArgMining 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp-22-attachments/2020.argmining-1.6.pdf
Code
 robinschaefer/climate-tweet-corpus