Topic Modeling and User Network Analysis on Twitter during World Lupus Awareness Day

Area of Science:

• Public Health
• Social Media Analysis
• Rheumatology

Background:

• Social media platforms, such as Twitter, are increasingly utilized for public health surveillance and insight discovery.
• Systemic lupus erythematosus (SLE) presents significant challenges in diagnosis and treatment, necessitating innovative approaches to patient support and information dissemination.

Purpose of the Study:

• To explore topics discussed on Twitter during World Lupus Day.
• To identify information most commonly shared by users and organizations regarding SLE.
• To recognize online influencers and opinion leaders in SLE discussions.

Main Methods:

• Analysis of tweet texts related to World Lupus Day.
• Latent topic extraction from user-generated content.
• Identification of online influencers and their communication strategies.

Main Results:

• Two distinct types of influencers emerged, utilizing different narrative approaches.
• Key themes and information priorities in online SLE discussions were identified.
• Hidden information valuable for healthcare decision-making was uncovered.

Conclusions:

• Social media data, particularly from Twitter, can provide actionable insights for healthcare decision-makers.
• Understanding online discourse and influencer roles is crucial for enhancing healthcare services for SLE patients.
• A model is proposed for healthcare organizations to detect and interpret hidden content in large text datasets.