Natural Language Processing for Large-Scale Analysis of Eczema and Psoriasis Social Media Comments

Abstract

Social media tools are widely used by dermatologic patients. Eczema and psoriasis, two of the most common inflammatory skin diseases, are well-represented on the social media site Reddit. We used natural language processing tools to examine comments in subreddits r/psoriasis and r/eczema (combined user base >187,000), tracking commenters’ interest levels and sentiments related to common treatments for psoriasis and eczema as well as discussions of adverse drug reactions. All comments from 2014–2020 from the subreddits r/eczema (n = 196,571) and r/psoriasis (n = 123,144) were retrieved and processed using natural language processing tools. Comment volume in r/eczema related to antibacterial therapies, lifestyle changes, and prednisone decreased from 2014–2020, whereas phototherapy comments remained stable, and dupilumab comment volume increased. Comment volume in r/psoriasis for newer therapeutics (including biologics and apremilast) increased after Food and Drug Administration approval, whereas older therapies such as etanercept, adalimumab, and methotrexate decreased over time. Sentiment scores tended to decrease in the years after Food and Drug Administration approval. Among psoriasis treatments, calcipotriene and branded calcipotriene/betamethasone foam had the highest sentiment, whereas apremilast had the lowest overall sentiment score. These analyses also identified changes in patient interest levels and sentiment related to eczema and psoriasis treatments, suggesting an area for additional research.