@inproceedings{kokkinakis-etal-2023-investigating,
title = "Investigating the Effects of {MWE} Identification in Structural Topic Modelling",
author = "Kokkinakis, Dimitrios and
Mu{\~n}oz S{\'a}nchez, Ricardo and
Bruinsma, Sebastianus and
Hammarlin, Mia-Marie",
editor = "Bhatia, Archna and
Evang, Kilian and
Garcia, Marcos and
Giouli, Voula and
Han, Lifeng and
Taslimipoor, Shiva",
booktitle = "Proceedings of the 19th Workshop on Multiword Expressions (MWE 2023)",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.mwe-1.7",
doi = "10.18653/v1/2023.mwe-1.7",
pages = "36--44",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Investigating the Effects of MWE Identification in Structural Topic Modelling
%A Kokkinakis, Dimitrios
%A Muñoz Sánchez, Ricardo
%A Bruinsma, Sebastianus
%A Hammarlin, Mia-Marie
%Y Bhatia, Archna
%Y Evang, Kilian
%Y Garcia, Marcos
%Y Giouli, Voula
%Y Han, Lifeng
%Y Taslimipoor, Shiva
%S Proceedings of the 19th Workshop on Multiword Expressions (MWE 2023)
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F kokkinakis-etal-2023-investigating
%X 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.
%R 10.18653/v1/2023.mwe-1.7
%U https://aclanthology.org/2023.mwe-1.7
%U https://doi.org/10.18653/v1/2023.mwe-1.7
%P 36-44
Markdown (Informal)
[Investigating the Effects of MWE Identification in Structural Topic Modelling](https://aclanthology.org/2023.mwe-1.7) (Kokkinakis et al., MWE 2023)
ACL