JMIR Publications

ABSTRACT

Background:

Endometriosis is a debilitating gynecological disease that is difficult to diagnose. Because of limited information and awareness, women often turn to social media (SM) to discuss disease-related concerns.

Objective:

The aim of the research was to apply computational techniques to SM posts to identify discussion topics about endometriosis and to find themes that require more attention from healthcare professionals and researchers.

Methods:

We retrospectively extracted posts from the Reddit environment r/Endo and r/endometriosis from January 2011 through April 2022. We utilized the fine-tuned BERT model on endometriosis posts for sentiment analysis and LDAMulticore algorithm for topics modeling.

Results:

A total of 45,693 Reddit posts and nearly 360 thousand comments were analyzed. Sentiment analysis revealed that 94% of posts were associated with negative sentiments and only 2.3% were expressing positive feelings. LDAMulticore revealed that the most popular topics of discussion were surgery, diagnosis, symptoms, and pain. Although endometriosis is a gynecological disease, there were also posts from men.

Conclusions:

This study shows that posts on SM platforms can provide insight into the concerns of women with endometriosis symptoms. Healthcare professionals can use this knowledge to understand which topics require more attention and which information to share with patients and to guide researchers in addressing the most urgent concerns of endometriosis patients. Healthcare professionals are also invited to participate more actively in SM discussions to share missing information and fill the necessary knowledge gaps about endometriosis diagnostics, treatment and co-morbidities.