Users' Concerns About Endometriosis on Social Media: Sentiment Analysis and Topic Modeling Study

Area of Science:

• Computational linguistics and social media analytics applied to women's health.
• Analysis of online patient communities for gynecological disease insights.

Background:

• Endometriosis is a challenging gynecological condition with limited awareness and difficult diagnosis.
• Women frequently use social media for support and to discuss endometriosis concerns.

Purpose of the Study:

• To identify key discussion themes about endometriosis on social media using computational methods.
• To assess the sentiment of online endometriosis discussions and identify areas needing more attention from healthcare providers and researchers.
• To explore positive themes within the endometriosis online community.

Main Methods:

• Retrospective analysis of 45,693 Reddit posts from r/Endo and r/endometriosis (January 2011 - April 2022).
• Application of machine learning techniques, including sentiment analysis and topic modeling.

Main Results:

• A significant increase in posts since 2011, with top categories including Questions, Rant/Vent, and Surgery-related topics.
• Over 92% of posts exhibited negative sentiment, with only 2.3% positive; no category had more positive than negative posts.
• Top topics identified were Surgery, Questions/Advice, Diagnosis, and Pain; Survey/Research was the least frequent topic.

Conclusions:

• Social media provides valuable insights into the daily struggles and concerns of women with endometriosis.
• The high volume of questions indicates a gap in physician-provided information, necessitating community support.
• Healthcare professionals and researchers should increase engagement to address patient needs, improve diagnosis, and disseminate scientific knowledge.