Abstract

Social media arguably have transformed the way people communicate about health. Research has documented that social media offer a forum for the expression of subjective experience, feelings, and personal management of illness, marking a groundbreaking shift from illness as a private experience, to the personalization of public health debates. Most studies, however, are focused on specific patient groups and forums dedicated to health and do not cover a broader range of postings, political debate, and information sharing on social media. With this backdrop, this paper explores the bigger picture of health communication on social media by harnessing machine learning methods including supervised classification and topic modeling applied to 280,000 Norwegian social media posts published on Twitter, Online Forums, and Instagram during the period 2012-2018. The results show that only one-third of the posts can be characterized as personalized communication. Furthermore, there are important differences across social media platforms—the forums being most personalized and Twitter being less personalized. The topic analysis reveals that health communication on social media reflects three sets of concerns—illness or health conditions, the health care system and its professionals, and life-styles issues—that display different levels of personalization across platforms and over time.

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