Annotation and Detection of Arguments in Tweets
Year: 2020
Type: other
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.
Source: Underline Science Inc.
DOI: 10.48448/e2xj-kt95
Authors: International Committee for Computational Linguistics 2020, Schaefer, Robin, Stede, Manfred
Institution: University of Potsdam
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6948036276