@inproceedings{4ac1cb7cb8154d4282b5e4502fe6530c,
title = "Cluster-Based BERTopic Modeling on Swedish COVID-19 Vaccine Posts",
abstract = "This paper explores the prevalent themes across multiple threads on the popular Swedish discussion forum Flashback. Among its diverse array of topics, the forum actively engages users in addressing and debating questions pertaining to COVID-19 vaccines and vaccination. Through distinguishing between positive and negative perspectives within posts across 14 relevant thread discussions, we employ BERTopic, a modular topic modeling framework, which utilizes pre-trained language models and applies clustering techniques to identify prevailing topics. This enables us to conduct a nuanced exploration of overarching themes, offering valuable insights into the multifaceted nature of the discussions regarding COVID-19 vaccines and vaccination in Sweden.",
keywords = "BERTopic, Swedish dataset, topic modeling, vaccination, vaccine",
author = "Dimitrios Kokkinakis and Hammarlin, {Mia Marie}",
year = "2024",
month = aug,
doi = "10.3233/SHTI240805",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "1906--1910",
editor = "John Mantas and Arie Hasman and George Demiris and Kaija Saranto and Michael Marschollek and Arvanitis, {Theodoros N.} and Ivana Ognjanovic and Arriel Benis and Parisis Gallos and Emmanouil Zoulias and Elisavet Andrikopoulou",
booktitle = "Digital Health and Informatics Innovations for Sustainable Health Care Systems - Proceedings of MIE 2024",
address = "Netherlands",
note = "34th Medical Informatics Europe Conference, MIE 2024 ; Conference date: 25-08-2024 Through 29-08-2024",
}
