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

Author:

Etebari Cameron AORCID,Braun Sterling EORCID,Vazquez-Machado Maria C,Butterworth James A

Abstract

Abstract Background Instagram (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. Objectives We sought to better characterize the source and content of PS-related posts on Instagram. Methods Metadata 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). Results Board-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%, P < .001), and board certification phrases distinguished their posts from other account types (23%, P < .001). Nonphysician posts focused on nonsurgical aesthetics like Botox and fillers (80%). However, nonplastics-trained physicians and organizations significantly contributed to procedural subcategories in a similar distribution to plastic surgeons. Conclusions Board-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

Publisher

Oxford University Press (OUP)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3