Who Posts on Instagram? Using Natural Language Processing to Assess the Relationship Between Training Background and Content of 700,000 Posts

Abstract

Abstract BackgroundInstagram (Menlo Park, CA) is a major platform for the dissemination of plastic surgery (PS) information, but the training background of users is difficult to ascertain. ObjectivesWe sought to better characterize the source and content of PS-related posts on Instagram. MethodsMetadata from publicly available Instagram posts containing PS relevant hashtags was collected from December 2018 to August 2020 using Node.js (Node.js Foundation, San Francisco, CA). The data was characterized by account type, and post topics were analyzed using a custom dictionary of PS procedures applied with natural language processing. All data analyses were performed with R (The R Foundation, Vienna, Austria). ResultsBoard-certified plastic surgeons account for 38% of posts on Instagram, followed by organizations (31%), nonplastics-trained physicians (19%), facial plastics (5%), oculoplastics (1%), and nonphysician providers (5%). Oculoplastics had the highest engagement rate with their posts (3.7 ± 5.1), whereas plastic surgeons had the lowest (2.7 ± 4.2). Breast aesthetics was the predominant topic posted by plastic surgeons (42%, PP ConclusionsBoard-certified plastic surgeons are not the predominant source of PS content on Instagram. Furthermore, posts by plastic surgeons have the lowest rate of engagement out of all account types studied. Although declarations of board certification distinguish content from plastics disciplines, they are only used in 21% of posts. Level of Evidence: 4