Why Is This Comment Shown First? The Algorithmic Decay of Public Discourse

Author’s Note

This article is, in some ways, a parenthesis — a step back from the broader themes of democracy, history, or policy to examine something quieter but just as corrosive: the slow decay of dialogue in the age of the algorithm.

It’s easy to dismiss comment sections as digital noise. But in an era where platforms curate what we see, what we feel, and even what we argue about, the structure of that noise matters. It shapes perception. It distorts consensus. It rewards outrage and leaves deliberation gasping for air.

I wrote this piece not out of nostalgia for “better conversations,” but from concern that our tools — once hailed as democratizing — are now subtly undermining the very habits that sustain democratic life. If we don’t reclaim the architecture of our public discourse, we risk losing more than civility. We risk losing clarity, common ground, and ultimately, the capacity to govern ourselves together.

This is not just about comments. It’s about what we choose to hear — and what we risk becoming if we stop choosing at all.

Social media platforms have transformed how we discuss politics, history, and current events. But while they promised a more open and democratic form of public discourse, they have instead given rise to a new kind of information environment—one governed not by norms of civility or truth, but by opaque algorithms designed to maximize engagement.

This shift has profound consequences for democratic conversation. One need not look further than the comment section of a typical Facebook post—in this case, from Le Monde, one of France’s leading newspapers—to observe the mechanisms by which engagement trumps deliberation.

A recent exchange on Le Monde’s Facebook page offers a striking illustration of how the architecture of online platforms subtly poisons the quality of public debate.

The post, written in French and discussing the treatment of prisoners during the war in Ukraine, drew two highly visible comments. The first, labeled by Facebook as “most relevant,” read:

“Et les prisons de Guantanamo gérées par les yankees, ainsi que les prisons ukrainiennes où sont incarcérés les prisonniers russes, ce sont des centres de vacances je crois !”
Translation: “And the Guantanamo prisons run by the Yankees, as well as the Ukrainian prisons where Russian prisoners are held—those must be vacation resorts, I guess!”

This anonymous commenter downplays alleged abuses by Russia by invoking a classic form of whataboutism: deflecting criticism by pointing to Western abuses, particularly those of the United States and Ukraine. The sarcastic tone implies moral equivalence—suggesting that Western democracies are no better, and thus have no grounds to criticize Russian behavior. The comment had only eight reactions and four replies.

And yet, Facebook’s algorithm marked it as “most relevant.”

Directly below, another user offered a simple but pointed response:

“Et certains vantent encore la Russie.”
Translation: “And yet some people still praise Russia.”

This brief remark received almost twice the engagement—14 reactions and 15 replies. It voiced concern over the normalization or justification of authoritarian regimes. But despite its greater traction, it was shown after the more provocative pro-Russian comment.

I. Engagement vs. Relevance

Why would a less popular and more controversial comment be given priority?

Because on Facebook, “relevance” is not determined by truth, factual rigor, or even majority consensus. Instead, it is computed by an algorithm designed to maximize user activity—clicks, replies, reactions. This system favors:

Controversy over consensus. Comments likely to stir debate, including disinformation, rise to the top.
Emotion over reflection. Sarcasm, anger, and irony outperform nuance and care.
Personalization over neutrality. Content is shown based on past behavior, reinforcing bubbles and biases.
Recency over depth. Newer comments can be prioritized even if older ones are more widely supported.

In short: provocation is rewarded.

II. The Democratic Cost of Algorithmic Polarization

This is not a minor flaw—it is a fundamental distortion of the public square. By encouraging outrage over deliberation, these platforms tilt the playing field in favor of extremism and cynicism. In such an environment, bad-faith actors thrive, while serious civic dialogue is drowned out.

We’ve seen this dynamic before, even if the medium was different. American history offers many examples: the echo chambers of the antebellum press, the red-baiting paranoia of the 1950s, or the culture wars amplified by talk radio in the 1990s. But in each of those cases, the structures driving division were visible and identifiable.

Today, the real danger is that we no longer see the strings.

III. The Trump Resurgence and the Algorithm in 2025

The corrosive dynamic described above has become particularly visible during Donald Trump’s return to the political stage in 2025. Having re-entered the White House amidst a storm of controversy and deep polarization, Trump has not only resumed his combative public persona but has also inaugurated a new era of algorithmic manipulation.

During his first 100 days, Trump has leveraged platforms like Truth Social, X (formerly Twitter), and Facebook with surgical precision—not simply to communicate with his base, but to game the mechanics of attention itself. Each post seems carefully crafted not for policy communication, but for maximum emotional and partisan impact. Conspiratorial language, ridicule of opponents, and explosive framing dominate his digital rhetoric.

More alarmingly, social media algorithms—still largely unregulated—have once again elevated this incendiary content to the forefront of millions of users’ feeds. Posts containing misleading claims about immigration, violent crime, or international affairs routinely outperform fact-based responses or official clarifications. The more inflammatory the message, the higher it climbs.

This isn’t merely a return to the tactics of 2016 or 2020—it’s their amplification. Trump’s digital team now openly embraces the logic of engagement-first communication, using A/B testing and bot-amplification to tilt the scales of visibility. Meanwhile, platforms—afraid of appearing partisan or losing conservative users—have backed away from meaningful content moderation.

The result? A feedback loop in which the most divisive voices are algorithmically boosted, while dissenting or moderating ones struggle to gain traction. We are watching, in real time, the transformation of digital spaces into echo chambers that reward outrage and punish nuance.

And once again, the invisible hand of the algorithm is not guiding us toward better information—but away from it.

IV. Reclaiming the Digital Commons

The Trump administration’s digital strategy may be its most revealing legacy—not because it is unique, but because it lays bare what the current system already rewards. If we continue to allow attention-maximizing algorithms to shape our collective discourse, we risk ceding the public square to those most adept at manipulating it.

But this is not inevitable. At a personal level, digital vigilance begins with small but meaningful habits: taking a moment before reacting, verifying sources before sharing, prioritizing long-form content over outrage bites, and refusing to reward the loudest voices in the room simply because they are loud. At a political level, we need far more than content moderation — we need transparency. Platforms should be legally required to disclose how their algorithms rank and surface content, and public institutions must invest in digital literacy as a civic skill, not just a technical one. The challenge is immense, but so is the cost of inaction.

The stakes are high. Comment sections may seem trivial, but they are symptoms of a larger problem: the slow corrosion of democratic discourse by systems optimized for engagement, not enlightenment.

We cannot afford to treat this as the natural state of online life. If we want to restore meaningful debate, we must hold platforms accountable for the ways they shape public opinion—and begin designing systems that privilege integrity over incitement.

Until then, we must each practice a kind of digital vigilance. And that starts with a single question—simple, but deeply revealing:

Why is this comment being shown to me first ?

Welcome to the conversation

US Politics and History is a blog for those who believe democracy deserves better than outrage,and history offers more than nostalgia. It’s a place to reconnect analysis with responsibility, and debate with decency.