title: Twitter analysis of the orthodontic patient experience with braces vs Invisalign.
abstract: OBJECTIVE
  To examine the orthodontic patient experience having braces compared with Invisalign by means of a large-scale Twitter sentiment analysis.
  
  
  METHODS
  A custom data collection program was created that collected tweets containing the words "braces" or "Invisalign" for a period of 5 months. A hierarchal Naïve Bayes sentiment analysis classifier was developed to sort the tweets into five categories: positive, negative, neutral, advertisement, or not applicable. Each category was then analyzed for specific content.
  
  
  RESULTS
  A total of 419,363 tweets applicable to orthodontics were collected. Users posted significantly more positive tweets (61%) than they did negative tweets (39%; P ≤ .0001). There was no significant difference in the distribution of positive and negative sentiment between braces and Invisalign tweets (P = .4189). Positive orthodontics-related tweets often highlighted gratitude for a great smile accompanied with selfies. Negative orthodontic tweets frequently focused on pain.
  
  
  CONCLUSIONS
  Twitter users expressed more positive than negative sentiment about orthodontic treatment with no significant difference in sentiment between braces and Invisalign tweets.
authors.forename: Daniel
authors.initials: D
authors.lastname: Noll
authors.forename: Brendan
authors.initials: B
authors.lastname: Mahon
authors.forename: Bhavna
authors.initials: B
authors.lastname: Shroff
authors.forename: Caroline
authors.initials: C
authors.lastname: Carrico
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Lindauer
mesh_terms: D001499:Bayes Theorem; D001915:Braces; D006801:Humans; D009968:Orthodontic Appliances, Removable; D009971:Orthodontics, Corrective / Q000295:instrumentation*; D017060:Patient Satisfaction; D061108:Social Media
keywords: Aligners; Braces; Clear; Experience; Invisalign; Twitter