A topic analysis method based on a three-dimensional strategic diagram

With the tremendous growth of scientific literature in recent years, methods of detecting and analysing research topics have become more and more important. This study proposes a topic analysis method combining latent Dirichlet allocation (LDA) and a three-dimensional strategic diagram. This study c...

Full description

Saved in:
Bibliographic Details
Published in:Journal of information science 2021-12, Vol.47 (6), p.770-782
Main Authors: Feng, Jia, Mu, Xiaomin, Wang, Wei, Xu, Ying
Format: Article
Language:English
Subjects:
Algorithms
Dirichlet problem
Health informatics
Medical research
Optimization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the tremendous growth of scientific literature in recent years, methods of detecting and analysing research topics have become more and more important. This study proposes a topic analysis method combining latent Dirichlet allocation (LDA) and a three-dimensional strategic diagram. This study constructs the three-dimensional strategic diagram by three dimensions of centrality, density and novelty, and we classify topics into seven categories according to their strategic positions. Using this topic analysis method, the paper analyses 62,340 publications in the field of medical informatics between 1991 and 2018. Results show that the research scope of medical informatics has become increasingly interdisciplinary. Data analytical methods and technologies are sub-domains with persistent popularity. New health technologies, drug safety, algorithm optimisation and standardisation of medical information are emerging research topics. We hope the findings could help researchers identify potential research topics and facilitate in-depth analysis of the current state of various fields.
ISSN:0165-5515
1741-6485
DOI:10.1177/0165551520930907