The purpose of this study was to examine the orthodontic patient experience with braces compared to Invisalign® by means of a large-scale Twitter sentiment analysis. A custom data collection program was created to collect tweets containing the words “braces” or “Invisalign.” A hierarchal Naïve Bayes sentiment classifier was developed to sort the tweets into one of five categories: positive, negative, neutral, advertisement, or not applicable. Among the 419,363 tweets applicable to orthodontics collected, users posted significantly more positive tweets (61%) than negative tweets (39%) (p-value = ® tweets (p-value=0.4189). In conclusion, Twitter users express more positive than negative sentiment about orthodontic treatment with no significant difference in sentiment between braces and Invisalign® tweets.
| Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-5238 |
| Date | 01 January 2016 |
| Creators | Noll, Daniel A |
| Publisher | VCU Scholars Compass |
| Source Sets | Virginia Commonwealth University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | © The Author |
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