Tweetorials were identified by searching “tweetorial” AND “Neurology or Neuro” on X. We created and validated a formula to determine the tweetorial “Impact Factor” (IF) that reflects retweets and likes to facilitate comparisons. Tweet and author characteristics were collected directly from the platform and internet search of academic profiles. We thematically analyzed each tweetorial to determine if it was “generalized” (topic relevant to all neurologists), “inclusive” (had utility to medical students or non-neurologist), and “clear” (topic stated in the first tweet).  The first tweet’s style was categorized as “humorous,” “creative,” “mystery case,” “question,” or “statement.” Generalized Estimating Equation was applied to account for author effects.