Abstract
PURPOSE: To determine whether Twitter improves dissemination of ophthalmology scientific publications METHODS: Data were collected on articles published on PubMed between the years 2016 and 2021 (inclusive) and identified with the word "ophthalmology". Twitter performance metrics, including the number of tweets, number of likes, and number of retweets were collected from Twitter using the publicly available scientific API. Machine learning and descriptive statistics were used to outline Twitter performance metrics. RESULTS: The number of included articles was 433710. The percentage of articles that were in the top quartile for citation count, which had ≥1 tweet was 34.4% (number 437/1270). Conversely, the percentage of articles that were in the top quartile for citation count, which had 0 tweets was 27.8% (number 12023/43244). When machine learning was used to predict Twitter performance metrics an AUROC of 0.78 was returned. This was associated with an accuracy of 0.97 CONCLUSION: This study has shown preliminary evidence to support that Twitter may improve the dissemination of scientific ophthalmology publications.