Mining the Twittersphere: Insights about Public Interest in Facial Reanimation Surgery from a Decade of Twitter Data

Abstract

Background With 500 million tweets posted daily, Twitter can provide valuable insights about public discourse surrounding niche topics, such as facial paralysis surgery. This study aims to describe public interest on Twitter relating to facial paralysis and facial reanimation surgery over the last decade. Methods Tweets containing the keywords “facial paralysis” and “Bell's palsy” posted between January 1, 2009, and January 1, 2019, were collected using Twitter Scraper. Tweets were screened by keywords relating to facial paralysis, and usage of these terms trended over time. Logistic regression was used to identify correlations between the quantity of publications per year and these terms posted on Twitter. Results 32,880 tweets were made during the study period, with no significant difference in the number of tweets per year. A very strong (r = 0.8–1.0) positive correlation was found between time and frequency of the term “plastic surgery” and “transfer” (p < 0.05). A strong (r = 0.60–0.79) correlation was found between time and frequency for the following terms: “facial reanimation,” “gracilis,” “masseter,” “plastics,” “transplant” (p < 0.05). A total of 619 studies with the keyword “facial reanimation” were published in PubMed within the study period. A very strong, positive correlation between publications per year and frequency was found for the terms “plastic surgery,” “function” and “esthetic,” and a strong, positive correlation was found for the “plastics,” “transplant,” “Botox,” “surgery,” “cosmetic,” “aesthetic” and “injection” (p < 0.05). Conclusions An increasing number of discussion about facial paralysis on Twitter correlates with increased publications and likely surgeon discourse on facial reanimation surgery, driving public interest.

Keywords

• facial paralysis
• facial reanimation
• twitter
• social media
• web scraping
• data mining