@inproceedings{4fd9277fe06b4689b6db2fa07ce4f1e2,
title = "Using Topic Modelling to Personalise a Digital Self-compassion Training",
abstract = "Young adults that struggle with mental health issues experience barriers to seek help. With our online self-compassion training we try to overcome some of these barriers. To improve our training, we can personalise exercises based on topic modelling. Data from a pilot study is used to analyse and evaluate the algorithm. Overall, the algorithm has an accuracy of 54.1% for predicting the right topic. This accuracy increases to 80.4% when considering an empty prediction to be correct as well. Although this research also shows that our data makes the task of topic modelling difficult, it does prove to be a possibility to personalise the designed training.",
keywords = "Mental health, Personalization, Self-compassion, Topic modelling",
author = "Lubbe, {Laura van der} and Nina Groot and Charlotte Gerritsen",
note = "Publisher Copyright: {\textcopyright} 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",
year = "2022",
month = mar,
day = "23",
doi = "10.1007/978-3-030-99194-4_32",
language = "English",
isbn = "978-3-030-99193-7",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer",
pages = "522--532",
editor = "Hadas Lewy and Refael Barkan",
booktitle = "Pervasive Computing Technologies for Healthcare",
address = "Germany",
edition = "1",
}