Digital Architecture of Social Media Platforms

 

By: Lilian H. Hill

 

The architecture of an environment is known to influence human behavior. The relationship between structure and agency extends beyond physical spaces and encompasses how individuals engage with and navigate online environments (Bossetta, 2018). How social media platforms are designed and mediated varies, and these differences influence people’s online activities. For example, some social media platforms favor visual communication, while others favor textual communication.

Bosetta (2018) divided the digital architecture of social media platforms into four key categories:

 

1. Network Structure can be defined as the way connections between accounts are established and sustained. It determines how connections between accounts are established and maintained. Social media enables users to connect with peers (“Friends” on Facebook, “Followers” on X [formerly known as Twitter]), as well as with public figures, brands, or organizations, which often operate specialized accounts with advanced tools (e.g., Facebook Pages, Instagram Business Profiles).

 

This structure influences three key aspects:

1. Searchability – How users discover and follow new accounts.
2. Connectivity – The process of forming connections. For example, Facebook’s mutual Friend model mirrors offline networks, while X’s one-way following system fosters networks with weaker real-life ties.
3. Privacy – Users' control over search visibility and connection interactions. Snapchat prioritizes private ties, while platforms like Instagram and X default to open networks but allow customizable privacy settings.

 

These elements shape the platform’s network dynamics, user relationships, and the content generated (Bosetta, 2018).

 

2. Functionality defines how content is mediated, accessed, and distributed on social media platforms. It encompasses five key components:

1. Hardware Access – Platforms are accessed via devices like mobiles, tablets, desktops, and wearables, influencing user behavior. For instance, tweets from desktops tend to show more civility than those from mobile devices.
2. Graphical User Interface (GUI) – The visual interface shapes navigation, homepage design, and interaction tools like social buttons (e.g., X Retweets, Facebook Shares), simplifying content sharing.
3. Broadcast Feed – Aggregates and displays content, varying in centralization (e.g., Facebook's News Feed) and interaction methods (e.g., scrolling vs. click-to-open).
4. Supported Media – Includes supported formats (text, images, videos, GIFs), size limits (character counts, video length), and hyperlinking rules.
5. Cross-Platform Integration – Enables sharing of the same content across multiple platforms.

 

These elements shape content creation, network behavior, and platform norms, influencing user expectations and interactions. Political actors, for example, must align with platform-specific norms to avoid appearing out-of-touch or inauthentic, which could harm their credibility and electability.

 

3. Algorithmic Filtering determines how developers prioritize posts’ selection, sequence, and visibility. This involves three key concepts:

1. Reach – How far a post spreads across feeds or networks, which algorithms can enhance or restrict.
2. Override – Pay-to-promote services, like Facebook's "boosting," allow users to bypass algorithms and extend a post's reach.
3. Policy – policies on fact-checking processes are subject to change, which permits the spread of fake news.

 

These factors are most relevant on platforms with one-to-many broadcast feeds (e.g., Facebook, X, Instagram). Platforms focused on one-to-one messaging (e.g., Snapchat, WhatsApp) are less affected by algorithmic filtering. However, when algorithms dictate content visibility, they influence users' perceptions of culture, news, and politics.

 

4. Datafication is how user interactions are transformed into data points for modeling. Every social media interaction leaves digital traces that can be used for advertising, market research, or improving platform algorithms. Maintaining a social media presence in political campaigns is less about direct interaction with voters and more about leveraging user data. Campaigns can analyze digital traces to inform persuasion and mobilization strategies.

 

Kent and Taylor (2021) commented that the design of many social media platforms limits meaningful discussions on complex issues. Deep, deliberative debates on complex problems like climate change or economic inequality are difficult on platforms optimized for advertising and data monetization.

References

Bossetta, M. (2018). The digital architectures of social media: Comparing political campaigning on Facebook, Twitter, Instagram, and Snapchat in the 201 6U.S. election, Journalism and Mass Communication Quarterly, 95(2), 471–496. https://doi.org/10.1177/1077699018763307

 Kent, M. L., & Taylor, M. (2021). Fostering dialogic engagement: Toward an architecture of social media for social change. Social Media + Society, 71(1). https://orcid.org/0000-0001-5370-1896