The Impact of Modeling Overall Argumentation with Tree Kernels

Henning Wachsmuth, Giovanni Da San Martino, Dora Kiesel, Benno Stein


Abstract
Several approaches have been proposed to model either the explicit sequential structure of an argumentative text or its implicit hierarchical structure. So far, the adequacy of these models of overall argumentation remains unclear. This paper asks what type of structure is actually important to tackle downstream tasks in computational argumentation. We analyze patterns in the overall argumentation of texts from three corpora. Then, we adapt the idea of positional tree kernels in order to capture sequential and hierarchical argumentative structure together for the first time. In systematic experiments for three text classification tasks, we find strong evidence for the impact of both types of structure. Our results suggest that either of them is necessary while their combination may be beneficial.
Anthology ID:
D17-1253
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Martha Palmer, Rebecca Hwa, Sebastian Riedel
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2379–2389
Language:
URL:
https://aclanthology.org/D17-1253
DOI:
10.18653/v1/D17-1253
Bibkey:
Cite (ACL):
Henning Wachsmuth, Giovanni Da San Martino, Dora Kiesel, and Benno Stein. 2017. The Impact of Modeling Overall Argumentation with Tree Kernels. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2379–2389, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
The Impact of Modeling Overall Argumentation with Tree Kernels (Wachsmuth et al., EMNLP 2017)
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PDF:
https://aclanthology.org/D17-1253.pdf
Video:
 https://aclanthology.org/D17-1253.mp4