Digital Health Discussion Through Articles Published Until the Year 2021: A Digital Topic Modeling Approach
Junhyoun Sung, Hyungsook Kim

TL;DR
This study analyzes digital health research trends up to 2021 across disciplines using topic modeling, revealing evolving themes, shared topics, and the impact of Covid-19 on research focus.
Contribution
It applies Latent Dirichlet Allocation to compare digital health topics across domains and time periods, highlighting research evolution and interdisciplinary overlaps.
Findings
Number of topics increased over time in all domains.
Shared themes include technology, medical issues, and social phenomena.
Covid-19 influenced research topics towards mental health and education.
Abstract
The digital health industry has grown in popularity since the 2010s, but there has been limited analysis of the topics discussed in the field across academic disciplines. This study aims to analyze the research trends of digital health-related articles published on the Web of Science until 2021, in order to understand the concentration, scope, and characteristics of the research. 15,950 digital health-related papers from the top 10 academic fields were analyzed using the Web of Science. The papers were grouped into three domains: public health, medicine, and electrical engineering and computer science (EECS). Two time periods (2012-2016 and 2017-2021) were compared using Latent Dirichlet Allocation (LDA) for topic modeling. The number of topics was determined based on coherence score, and topic compositions were compared using a homogeneity test. The number of optimal topics varied…
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Taxonomy
TopicsComputational and Text Analysis Methods · Social Media in Health Education
