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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 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.
