1. Twitter analysis of the orthodontic patient experience with braces vs Invisalign.
- Author
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Noll D, Mahon B, Shroff B, Carrico C, and Lindauer SJ
- Subjects
- Bayes Theorem, Humans, Braces, Orthodontic Appliances, Removable, Orthodontics, Corrective instrumentation, Patient Satisfaction, Social Media
- Abstract
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 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., Conclusion: Twitter users expressed more positive than negative sentiment about orthodontic treatment with no significant difference in sentiment between braces and Invisalign tweets.
- Published
- 2017
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