The feeling of deep societal division is an artifact of platform design. Algorithms amplify extreme voices because they generate engagement, creating a false impression of widespread polarization. In reality, without these amplified voices, most people's views on contentious topics are quite moderate.

Algorithms optimize for engagement, and outrage is highly engaging. This creates a vicious cycle where users are fed increasingly polarizing content, which makes them angrier and more engaged, further solidifying their radical views and deepening societal divides.

Threads' leadership intentionally avoids optimizing for vanity metrics like "time spent." For example, they refuse to add a vertical video feed because it would conflict with their core goal of being the "best app for public conversation," choosing instead to measure proxies for conversational depth, like reply chains.

Social media content that "dunks on" an opposing group is 67% more likely to be shared. This virality is driven by in-group reinforcement, not by persuading outsiders. The platform's algorithm rewards and encourages this divisive behavior.

The addictiveness of social media stems from algorithms that strategically mix positive content, like cute animal videos, with enraging content. This emotional whiplash keeps users glued to their phones, as outrage is a powerful driver of engagement that platforms deliberately exploit to keep users scrolling.

Algorithmic feeds on platforms like X (formerly Twitter) are powerful engines of polarization. They flatten nuanced, multi-faceted political issues into a single left-vs-right dimension. This forces users into partisan camps and punishes heterodox thinking, as any deviation from the party line is suppressed by the algorithm and attacked by users.

Cross-posting identical content to X and Threads elicits wildly different reactions, with one platform leaning heavily left and the other right. This demonstrates the deep political siloing of online discourse, where each platform caters to and reinforces a specific ideological viewpoint.

Threads' goal to be a more civil platform has successfully differentiated it from the 'hyper-polarized' X. However, this moderation comes at a cost: it lacks the high-conflict conversations that drive news cycles and cultural relevance, which still happen on its more chaotic rivals.

Social media algorithms reward content that triggers high-arousal emotions like anger, fear, and awe, as these lead to engagement. Contentment, a low-arousal state, doesn't prompt users to click or share, so it is systematically de-prioritized, favoring rage bait.