A replication and extension of the Personal Social Media Ecosystem Framework

The recently forwarded Personal Social Media Ecosystem Framework (PSMEF) allows researchers to study social media in terms of generalized types of user interfaces. This study formally extended the PSMEF via the Digital User Interface Model and replicated previous work by evidencing the existence of new (e.g., Overtly Algorithmic Content Pages) and validating previously identified types of user interfaces (e.g., Home Pages and Chats/Messages) that make up individuals' personal social media environments. Using topic modeling (i.e., Latent Dirichlet Allocation) and a novel mixed methods approach (i.e., schematic semantic network analysis), we quantitatively evidenced four distinct classes of user interfaces based on open-ended descriptions that participants provided for six popular social media platforms (i.e., Instagram, Snapchat, Facebook, Twitter, TikTok, and YouTube). Results inform on the qualitative differences between distinct user interface classes that underwrite users' experiences over social media, with implications for conceptualization and operationalization related to social media use. Social media is constantly changing. Feature updates, the rise of new platforms, and the introduction of novel spaces for users to engage within online (e.g., For You Page on TikTok) have all made it harder to study social media. By taking a new approach to investigating social media as a digital ecosystem made up of various online places, we analyzed participant descriptions of spaces they typically used and identified four core types of online spaces characterizing six popular social media platforms. Some of these characteristic spaces provide access to content from a user's social contacts (i.e., Home Pages) or function as a venue for direct messaging (i.e., Chats/Messages). Others enable users to search and/or explore content, largely external to their social network (i.e., Search Pages, Overtly Algorithmic Content Pages). Results help to advance a flexible basis to approach the study of social media effects across platforms as they evolve over time-specifically, by providing initial evidence for the existence of different types of characteristic spaces permeating social media as a digital landscape.