Investigating the Effects of MWE Identification in Structural Topic Modelling
Dimitrios Kokkinakis, Ricardo Muñoz Sánchez, Sebastianus Bruinsma, Mia-Marie Hammarlin
Abstract
Multiword expressions (MWEs) are common word combinations which exhibit idiosyncrasies in various linguistic levels. For various downstream natural language processing applications and tasks, the identification and discovery of MWEs has been proven to be potentially practical and useful, but still challenging to codify. In this paper we investigate various, relevant to MWE, resources and tools for Swedish, and, within a specific application scenario, namely ‘vaccine skepticism’, we apply structural topic modelling to investigate whether there are any interpretative advantages of identifying MWEs.- Anthology ID:
- 2023.mwe-1.7
- Volume:
- Proceedings of the 19th Workshop on Multiword Expressions (MWE 2023)
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Archna Bhatia, Kilian Evang, Marcos Garcia, Voula Giouli, Lifeng Han, Shiva Taslimipoor
- Venue:
- MWE
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 36–44
- Language:
- URL:
- https://aclanthology.org/2023.mwe-1.7
- DOI:
- 10.18653/v1/2023.mwe-1.7
- Cite (ACL):
- Dimitrios Kokkinakis, Ricardo Muñoz Sánchez, Sebastianus Bruinsma, and Mia-Marie Hammarlin. 2023. Investigating the Effects of MWE Identification in Structural Topic Modelling. In Proceedings of the 19th Workshop on Multiword Expressions (MWE 2023), pages 36–44, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- Investigating the Effects of MWE Identification in Structural Topic Modelling (Kokkinakis et al., MWE 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2023.mwe-1.7.pdf