Sentiment analysis and natural language processing using Reddit data to evaluate patient opinions on hair loss therapeutics (Preprint)

Author:

Sally RachelORCID,Shapiro Jerry,Lo Sicco Kristen

Abstract

BACKGROUND

Online forums are rich sources of user-derived data and harnessing this information utilizing natural language processing techniques can provide insights into patient experiences. The subject forums of Reddit may allow for focused explorations such as opinions on specific therapeutic agents.

OBJECTIVE

To determine patient sentiment about key treatments for female hair loss. Secondarily, to demonstrate the feasibility of using Reddit data to perform sentiment analysis on patient comments.

METHODS

A software pipeline scraped publicly available Reddit comments from r/femalehairloss, then processed them into sentence tokens. Sentiment analysis was subsequently performed. A frequency word representation was created.

RESULTS

The most frequently cited single treatments were minoxidil and spironolactone. Comments mentioning PRP and minoxidil were the second and third most positive on average. Comments referencing dutasteride were the most positive, however, this may be skewed by the low number of dutasteride-only comments. Finasteride comments were the least positive on average but were still slightly greater than 0.

CONCLUSIONS

In this paper, we have demonstrated the feasibility of performing sentiment analysis on Reddit comments. Our results suggest that opinions about hair loss therapeutics on the examined forum were on average positive. Analysis of health-focused subreddits such as r/femalehairloss can provide a deeper understanding of patient discourse and may also represent an opportunity for physicians to disseminate evidence-based recommendations.

Publisher

JMIR Publications Inc.

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