Twitter analysis of the orthodontic patient experience with braces vs Invisalign

Objective: To examine the orthodontic patient experience having braces compared with Invisalign by means of a large-scale Twitter sentiment analysis. Materials and 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 Naive 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. Conclusion: Twitter users expressed more positive than negative sentiment about orthodontic treatment with no significant difference in sentiment between braces and Invisalign tweets.