Posts with health content are shared on social networking sites by government agencies, fan clubs or social marketers on a daily basis. These posts play an important role in informing people and linking them on social networks in order to share their ideas, change their behavior, or contribute to their diseases. Despite the prominence of the role of social networks in social marketing, so far this field has not been formally analyzed in the literature. Therefore, the purpose of this study is to provide a formal analysis of posts with health content and to propose a framework for categorizing them based on their message content. With this in mind, the study performed qualitative content analysis involving three interrelated coding procedures. First, the study reviewed earlier works in the social marketing literature and more recent analysis of the function of social networks to improve health to identify initial coding categories (deductive coding). Second, the study drew together systematic inferences from a purposive sample of health-subject posts (n = 342) to derive initial coding categories (inductive coding). Finally, the study implemented a double-coding procedure on a probabilistic sample of health-subject posts (n = 264) to validate the initial coding categories (validation coding). Collectively, the three coding procedures produced 7 exhaustive and mutually exclusive categories of health-subject posts. The proposed classification provides a comprehensive framework for thinking about posts with health content. For social marketers, it provides guidance to create the stream of content necessary to stimulate daily interactions in social media channels. For researchers, it offers a solid conceptual foundation to categorize and measure health-subject posts.