In 2025, one sentence is frequently heard on LinkedIn: “I’m doing the same things as before… but no one sees my posts anymore.”

Behind this frustration lies a deeper and more important question than a simple issue of reach: is visibility truly equitable on professional social networks?

This debate intensified in recent weeks following a series of experiments conducted by women who modified gender-coded elements or tone in their profiles or writing style, and observed a marked increase in the visibility of their posts. The Financial Times notably reported cases where creators said they saw their impressions rise significantly after adopting so-called “gender swaps” or “bro-coding” in their language.

TechCrunch later added nuance: the story is more complex than “LinkedIn is sexist,” but the feeling of a widespread drop in visibility is very real among many creators.

So what is really happening? And more importantly: how can brands and organizations navigate these dynamics without chasing the algorithm at all costs?

What an Algorithm Does—and Doesn’t Do

A newsfeed algorithm is not an arbiter of “merit.” It is a predictive system designed to determine what will capture attention, generate interactions, and satisfy the user.

On LinkedIn, signals such as the time spent on a post (often referred to as dwell time) are among the indicators used to rank content. LinkedIn has explained this in an engineering blog post: the platform analyzes reading behavior (time spent) and uses it as a signal, notably penalizing content that is skimmed too quickly.

As a result, the algorithm amplifies forms of communication that quickly trigger reading, reactions, and comments — not necessarily those that are the most nuanced, the most inclusive, or the most useful.

Why Visibility Equity Becomes an Economic Issue

On a network like LinkedIn, visibility is directly tied to opportunities: partnerships, recruitment, inbound inquiries, and perceived credibility. These “gender experiments” resonated strongly because they highlight a central issue: the economic value of visibility.

However, caution is warranted before drawing quick conclusions. LinkedIn states that it does not use gender as a ranking factor and instead points to the overall increase in the volume of content being published.

This leads to a more plausible — and more useful — hypothesis: algorithms can amplify biases that already exist in human behavior and social norms. In other words, they do not create these imbalances; they simply make them more visible and more powerful.

A concrete example: if certain ways of expressing ideas — more assertive, more “authoritative,” or more self-promotional — generate higher engagement, they are gradually promoted by the algorithm, to the detriment of other forms of discourse. As a result, more cautious, nuanced voices, or those less inclined toward self-promotion, may be structurally disadvantaged, even without any explicit intent.

LinkedIn vs. X: When Engagement Becomes a Filter on Reality

On X (formerly Twitter), academic research and empirical observations converge on one point: emotionally charged and conflict-driven content performs well. Studies show that dynamics of outrage and animosity (“outrage,” out-group animosity) are strongly correlated with engagement.

More recently, research cited by The Guardian indicates that even a slight increase in exposure to partisan or divisive content in the “For You” feed can accelerate affective polarization in a very short period of time.

These findings are particularly relevant because visibility equity does not depend solely on a hidden algorithmic parameter; it also depends on what platforms reward and what we, as users, reinforce through our clicks.

The Real Risk for Brands: Optimizing for the Algorithm… and Losing Identity

When reach declines, the temptation is strong to:

• adopt a sharper tone that generates reactions;
  
  
• publish more frequently without a clear editorial direction;
  
  
• follow formats that “work,” even if they do not reflect the brand’s identity.
  

In the short term, this approach can revive visibility. In the long term, it comes at a high cost: trust, coherence, and reputation.

The objective, therefore, is not to “escape” the algorithm, but to understand it well enough to remain intentional.

A Simple Compass: Working With Signals, Not Against Your Values

Here is a concrete approach that brands, leaders, and organizations can apply right away:

1) Prioritize Clarity Over Volume

If dwell time matters, value often comes from a clear point, a precise example, or an idea that prompts reflection. LinkedIn indicates that it considers the quality of reading and exchanges when promoting content. Focus on posts that invite attentive reading and thoughtful comments, rather than quick, superficial reactions.

2) Replace “Strong” Opinions With Well-Founded Positions

On X, content that triggers indignation — meaning reactions of anger, rejection, or confrontation — often generates more engagement.

On LinkedIn, a tone of certainty may also be rewarded because it provokes reactions. However, attention can be earned in other ways: data, real-world insights, mini case studies, or lessons drawn from mistakes.

3) Build Distribution, Not Just Publication

Visibility equity is also shaped outside the algorithm: content partnerships, employee advocates, cross-collaborations, newsletters, and events. Reducing dependence on the newsfeed helps create greater stability.

4) Measure Impact Beyond Impressions

Impressions are not the most relevant key performance indicator. Track inbound inquiries, the quality of conversations, cycle time, recruitment outcomes, and qualified leads. Lower reach paired with higher conversion is far more valuable than empty virality.

What if We Framed Equity as a Collective Choice?

The debate around algorithms and equity is not purely technical; it is cultural. Which narratives are valued? Which voices are legitimized? Which formats are encouraged?

Platforms have a role to play — in transparency, design, and governance — but brands and communities do as well: amplifying useful voices, encouraging constructive conversations, and promoting content that elevates the discourse rather than inflaming the feed.

As the year comes to a close, this may be the healthiest moment to ask the question:

in 2026, do we want to be simply more visible — or more fair, coherent, and useful?

Because ultimately, the best strategy is not to “beat the algorithm.”

It is to build a presence that endures, even as the algorithm changes.