Multimodal Argument Mining: A Case Study in Political Debates

Eleonora Mancini, Federico Ruggeri, Andrea Galassi, Paolo Torroni


Abstract
We propose a study on multimodal argument mining in the domain of political debates. We collate and extend existing corpora and provide an initial empirical study on multimodal architectures, with a special emphasis on input encoding methods. Our results provide interesting indications about future directions in this important domain.
Anthology ID:
2022.argmining-1.15
Volume:
Proceedings of the 9th Workshop on Argument Mining
Month:
October
Year:
2022
Address:
Online and in Gyeongju, Republic of Korea
Editors:
Gabriella Lapesa, Jodi Schneider, Yohan Jo, Sougata Saha
Venue:
ArgMining
SIG:
Publisher:
International Conference on Computational Linguistics
Note:
Pages:
158–170
Language:
URL:
https://aclanthology.org/2022.argmining-1.15
DOI:
Bibkey:
Cite (ACL):
Eleonora Mancini, Federico Ruggeri, Andrea Galassi, and Paolo Torroni. 2022. Multimodal Argument Mining: A Case Study in Political Debates. In Proceedings of the 9th Workshop on Argument Mining, pages 158–170, Online and in Gyeongju, Republic of Korea. International Conference on Computational Linguistics.
Cite (Informal):
Multimodal Argument Mining: A Case Study in Political Debates (Mancini et al., ArgMining 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-3/2022.argmining-1.15.pdf
Code
 federicoruggeri/multimodal-am