From Social Walls to Personalized “For You” Systems
The digital landscape has evolved subtly yet profoundly, with social media consumption growing and permeating various demographic groups. Richard Rogers, Director of the Digital Methods Initiative at the University of Amsterdam, describes this shift where the focus has moved from debating the importance of social media to understanding how they operate, what they capture, and prioritize when users engage with them.
The Rise of “Post-Social Media” Era
Rogers introduces the term “post-social media” to describe an era dominated by algorithmic feeds that have replaced the traditional social media feed based on friends’ posts. This new phase is characterized by “For You” systems that recommend content at scale, interpreting micro-signals like pausing to view an item briefly or stopping the scroll as indicators of user interest.
Micro-Signals and User Behavior
In these systems, content displayed on screen originates from small, repeated signals derived from user behavior. Rogers explains that preferences are inferred from what users view and micro-behaviors such as pausing over content, briefly glancing at it, or hovering the cursor. These subtle signals are interpreted as user intent, even when users believe their interaction was casual.
Sustaining Consumption through Algorithmic Design
The ultimate goal of this fine-grained signal analysis is to maintain user engagement. Rogers highlights that algorithms are designed to deliver content users like and also content that may cause discomfort, framing it as a crucial aspect of the “attention economy.” Users consume pieces they might not openly admit to being interested in, and the system logs and re-presents them, creating a diverse yet eclectic content mix that broadens paths for retaining user attention.
The Algorithm Takes Center Stage in Content Distribution
Rogers identifies this pattern on specific platforms like TikTok, X (formerly Twitter), YouTube Shorts, and Instagram Reels. Here, content is presented as an infinite sequence of short units designed for quick consumption, prioritizing continuity over pauses.
Cultural Shift and the Decline of Open Internet
According to Rogers, this distribution method drives a broader cultural change. The open internet—publicly accessible, interoperable web based on open standards, not controlled by a single platform—loses ground as traffic and activity concentrate within closed-environment platforms with their own rules and internal circulation mechanisms.
Shifting Content Production Dynamics
Rogers acknowledges the growing influence of professional content creators who have learned to navigate feeds and engage followers to maintain a fanbase. This professionalization combines format knowledge, publishing discipline, and performance signal interpretation within the platform.
Algorithmic Systems Shape Content Consumption
Despite content creators’ professionalization, Rogers emphasizes that the real content distribution concentration lies in recommendation systems. These systems interpret consumption signals and push content more likely to retain user attention, shaping what people ultimately view on algorithm-driven platforms.
Cultural Diagnostics and User Habits
As these feeds grow in popularity, cultural diagnostics emerge to describe common user experiences. Concepts like “doom scrolling” and “brain rot” illustrate the habit of consuming negative or trivial content in an endless scroll, leading to perceived anxiety and degradation of attention and critical thinking—compared by Rogers to consuming junk food and feeling trapped in the content flow.
Attention Fabrication through Algorithms
The technical operation behind this model aims to create engagement. According to Rogers, attention is generated through systems that learn from consumption signals, adjust content order, and maintain consumption continuity. This transforms the feed into an inference engine testing combinations and reinforcing repetition patterns, resulting in a practical outcome.
Key Questions and Answers
- What is the new era of digital consumption described by Richard Rogers? It’s the “post-social media” era, characterized by algorithmic feeds that prioritize user engagement through fine-grained signal analysis.
- How do these new systems interpret user behavior? They analyze micro-signals like pausing to view content briefly or stopping the scroll, interpreting them as user intent.
- What is the goal of these algorithmic systems? Their primary objective is to sustain user engagement by delivering content users like and also content that may cause discomfort.
- Which platforms exemplify this shift? TikTok, X (formerly Twitter), YouTube Shorts, and Instagram Reels showcase this new content distribution model.
- What broader cultural changes does this shift imply? It leads to a decline in the open internet and an increase in closed-environment platforms, altering content production dynamics.
- How do recommendation systems shape content consumption? They interpret consumption signals and prioritize content more likely to retain user attention, determining what people ultimately view.
- What are some negative consequences of this new consumption model? Concepts like “doom scrolling” and “brain rot” describe the habit of consuming negative or trivial content, leading to perceived anxiety and degradation of attention and critical thinking.
