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	title        = {The Prevalence of mRNA Related Discussions during the Post-COVID-19 Era},
	abstract     = {Vaccinations are one of the most significant interventions to public health, but vaccine hesitancy and skepticism are raising serious concerns for a portion of the population in many countries, including Sweden. In this study, we use Swedish social media data and structural topic modeling to automatically identify mRNA-vaccine related discussion themes and gain deeper insights into how people’s refusal or acceptance of the mRNA technology affects vaccine uptake. Our point of departure is a scientific study published in February 2022, which seems to once again sparked further suspicion and concern and highlight the necessity to focus on issues about the nature and trustworthiness in vaccine safety. Structural topic modelling is a statistical method that facilitates the study of topic prevalence, temporal topic evolution, and topic correlation automatically. Using such a method, our research goal is to identify the current understanding of the mechanisms on how the public perceives the mRNA vaccine in the light of new experimental findings.},
	booktitle    = { Caring is Sharing – Exploiting the Value in Data for Health and Innovation / M. Hägglund et al. (eds.) Proceedings of the 33rd Medical Informatics Europe Conference (MIE2023), Gothenburg, Sweden, 22-25 May 2023},
	author       = {Kokkinakis, Dimitrios and Bruinsma, Sebastianus Cornelis Jacobus  and Hammarlin, Mia-Marie},
	year         = {2023},
	publisher    = {IOS Press},
	ISBN         = {978-1-64368-388-1},

	title        = {Investigating the Effects of MWE Identification in Structural Topic Modelling
	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, we apply structural topic modelling to investigate whether there are any interpretative advantages of identifying MWEs.},
	booktitle    = {The 19th Workshop on Multiword Expressions (MWE 2023)},
	author       = {Kokkinakis, Dimitrios and Muñoz Sánchez, Ricardo and Bruinsma, Sebastianus C. J. and Hammarlin, Mia-Marie},
	year         = {2023},
	publisher    = {ACL},
	ISBN         = {978-1-959429-59-3},