JMIR Publications

ABSTRACT

Background:

There are more than 6000 rare diseases in existence today, with the number of patients suffering from such conditions rapidly expanding. Most research to date has focused on the diagnosis, treatment and development of orphan drugs, while few studies have examined the topics and emotions expressed by patients living with rare diseases on social media platforms, especially on online health communities.

Objective:

This study aims to detect the topic categorizations and sentiment polarity for albinism on a Chinese Online Health Community (OHC), Baidu Tieba, using multiple methods. The OHC was deeply mined using topic mining, social network analysis, and sentiment polarity analysis. Through these methods, we determined the current situation of community construction, identifying the ongoing needs and problems experienced by albinism patients in their daily lives.

Methods:

We use the Albinism community on the Baidu Tieba platform as the data source in this study. Term Frequency – Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) models, and Navie Bayes (NB) were employed to mine the various topic categories. Social network analysis was employed to analyze the evolution of the albinism community, which was completed using the Gephi tool. Sentiment polarity analysis was performed using a long short-term memory algorithm.

Results:

We identified 8 main topics discussed in the community, including: daily sharing, family, interpersonal communication, social life and security, medical care, occupation/education, beauty and self-care. Among which, daily sharing held the largest proportion of discussions. From 2012 to 2019, the average degree and clustering coefficient of the albinism community continued to decline, while the network center transferred from core communities to core users. A total of 68.42% of the corpus was emotional, with 55.87% being positive and 32.55% negative. Negative emotions were twice as high as positive emotions in social life and security.

Conclusions:

The study reveals insights into the emotions expressed by albinism patients on the Chinese OHC, Baidu Tieba, providing healthcare practitioners with greater appreciation of current emotional support and patient experiences. Current OHCs do not exert enough influence due to scarcity of effective organization and development. Healthcare sectors should take greater advantage of OHCs to support vulnerable patients of rare diseases to meet their evidenced needs.