| Issue |
BIO Web Conf.
Volume 174, 2025
2025 7th International Conference on Biotechnology and Biomedicine (ICBB 2025)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 5 | |
| Section | Technologies and Methodologies in Biomedical Research | |
| DOI | https://doi.org/10.1051/bioconf/202517403004 | |
| Published online | 12 May 2025 | |
Disease Spectrum Analysis and Population Health Trend Research Based on Text Data Analysis of Large-Scale Online Medical Consultation
1 The Vanguard Group, Charotte, NC 28262, USA
2 TikTok Pte. Ltd, San Jose, CA 95110, USA
3 Google LLC, Mountain View, CA 94043, USA
* Corresponding author: yyuhao10@gmail.com
This study investigates common health problems and online healthcare seeking behavioral patterns of individuals using a large-scale online consultation dataset extracted from well-known healthcare platforms. By using text mining techniques, including tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, and topic modeling, we analyzed the textual content of these consultations to identify key themes and patterns. Our findings suggest that there are significant gender differences in online medical counseling, with women more likely to seek medical advice online than men. Additionally, the analysis identified age-related patterns of health concerns, with younger people primarily reporting minor illnesses, while older people expressed concerns about chronic conditions. These results highlight the importance of understanding the unique healthcare needs of different populations and the potential role of online platforms in meeting those needs. This study provides valuable insights into the common health concerns and patterns of online healthcare seeking behavior among individuals.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.