A Framework for Categorizing Social Media Posts

Abstract

Brand posts represent a recurrent and concise updates authored by brands and sent out to their followers in social media channels. Brand posts play a crucial linking role, connecting brands to their customers and fans on a daily basis. Despite their prominence in establishing an effective social media presence, brand posts have not been subject to formalized analyses in the marketing literature. The purpose of this study is, therefore, to conduct a formalized analysis of brand posts and 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 advertising literature and more recent analyses of brand posts in the social media literature to identify initial coding categories (deductive coding). Second, the study drew together systematic inferences from a purposive sample of brand posts (n=371) to derive initial coding categories (inductive coding). Finally, the study implemented a double-coding procedure on a probabilistic sample of brand posts (n=249) to validate the initial coding categories (validation coding). Collectively, the three coding procedures produced 12 exhaustive and mutually exclusive categories of brand posts. The proposed categorization offers a comprehensive framework to think about brand posts. For marketers, it provides guidance to create the stream of content necessary to stimulate daily consumer interactions in social media channels. For researchers, it offers a solid conceptual foundation to categorize and measure brand posts.