Sentiment Analysis Surrounding Blepharoplasty in Online Health Forums

Abstract

Background: Upper and lower blepharoplasty are among the most common procedures in aesthetic surgery and are often emotionally laden due to the subjective nature of outcomes and implications with beauty and self-identity. This article capitalizes on the increasing wealth of patient-provided health information online and is the first to analyze the emotions surrounding blepharoplasty discussions in an open internet health forum, MedHelp. Methods: We used Python to scrape MedHelp for threads that contained “blepharoplasty” and then used IBM Watson Natural Language Understanding to perform sentiment analyses, calculating a general sentiment score (−1 to +1) as well as emotion scores for anger, sadness, joy, fear, and disgust (0 to 1) for posts and keywords contained within the posts. Keywords were then manually grouped into five distinct clinical categories: symptoms, doctor, treatment, medication, and body. Results: We collected 52 threads containing “blepharoplasty,” yielding 154 posts and 1365 keywords. The average sentiment score was negative among all posts (−0.15) and keywords (−0.30). Among all posts and keywords, sadness had the highest score and disgust had the lowest score. Conclusions: Fear and sadness are the predominant emotions for blepharoplasty patients online, and the most negative symptoms cited are not ones that surgeons typically expect.

Mengukur Dampak Investasi Berkelanjutan: Evaluasi Terhadap Faktor ESG dalam Portofolio Investor

“…Analisis sentimen juga berperan dalam mengevaluasi efektivitas kebijakan pajak dan inisiatif pemerintah. Dengan menganalisis tren sentimen sebelum dan sesudah implementasi kebijakan, para peneliti dapat menilai apakah reformasi pajak telah mencapai tujuan yang diharapkan dan apakah reformasi pajak memiliki konsekuensi yang tidak diharapkan terhadap sentimen public (Lu et al, 2022;Mello et al, 2022).…”