Better Understand Rare Disease Patients' Needs by Analyzing Social Media Data - a Case Study of Cystic Fibrosis

There are approximately 7,000 rare diseases, and 25-30 million people affected with a rare disease in the United States. Prevalence rate for rare diseases is relatively low compared to common diseases. Thus, disease rarity leads to a lack of clinical familiarity that often impedes accurate and timely diagnosis for many rare disease patients. Social media has become an important resource/tool for discussing, sharing, and seeking information relevant to rare diseases by patients and families. In this study, we aimed to analyze rare disease-related posts from Reddit, one popular social media platform to reveal rare disease patients' needs based on hidden topics to be identified. We implemented NLP/topic modelling to identify main topics from the posts and consequently computed TF-IDF to detect the most prevalent phrases as sub-topics from the posts. As a proof of concept, we primarily focused on Cystic Fibrosis as a case study to demonstrate the use of data from Reddit for rare disease research.