DAre your LinkedIn followers viewing you as a “thought leader”? Do numerous commenters laud your strategies for “scaling” your startup? Do recruiters slide into your DMs “to explore potential synergies”?

If the answer is no, it could be tied to your gender.

Multiple women took part in an experiment on LinkedIn this week, sparked by viral posts suggesting that altering one’s gender to “male” could enhance visibility on the platform.

Others have reported that by modifying their profiles and using business jargon like “drive,” “transform,” and “accelerate,” they experienced an uptick in engagement.

This surge in engagement has led some to speculate that LinkedIn’s algorithm may harbor biases, making men who utilize typical business language more visible.

Similar to many large social media platforms, LinkedIn employs algorithms to determine which posts reach users, elevating some while downgrading others.

In a blog post last Thursday, LinkedIn acknowledged this phenomenon but stated it doesn’t factor in “demographic information” when deciding who receives visibility. Instead, they mentioned that “hundreds of signals” contribute to a post’s performance.

“Changing your profile gender does not influence how your content is displayed in searches or your feed,” a representative stated. Yet, anecdotes continue to circulate.

“It was quite thrilling,” shared Simone Bonnet, a social media consultant based in Oxford, who altered her pronouns to “he/him” and updated her name to “Simon E.” on LinkedIn earlier this week.

“Right now, I’m witnessing a staggering 1,600% increase in profile views, a significant figure given our current social media engagement. We’re also observing a 1,300% rise in impressions, with similar trends in reach statistics.”

Megan Cornish, a communications strategist at a mental health tech firm, began experimenting with her LinkedIn profile after noticing a drop in her reach earlier this year.

Initially, she changed her gender to “male.” Then, she utilized ChatGPT to rewrite her profile in a “male-coded” manner, drawing from a LinkedIn post that suggested favoring “agency” words like “strategic” and “leader.”

Lastly, she prompted ChatGPT to revamp an old, underperforming post from months prior using similarly “agent-like” language to discern how “peer coding” was influencing reach.

The results were favorable. Shortly after, her LinkedIn reach soared by 415% in the week following the changes. She penned an article about her experience, which went viral, gathering nearly 5,000 interactions.

However, she disliked the outcome. Previously, she described her posts as “soft,” combining “succinctness and intelligence with warmth and humanity.” Now, as “Brother Megan,” she felt assertive and confident, “akin to a white man strolling about.”

She decided to stop after a week. “I had initially intended to do this for an entire month. Each day, as things improved, I became increasingly irritated.”

Not every individual shared the positive experiences of Cornish and Bonnet. Cath Cooper, a technology and social media writer, stated she changed her gender to “male” and later identified her race as “white” (despite being Black). She reported a decline in her profile’s reach and engagement. Other women of color on the platform recounted similar experiences here.

“We understand that algorithms have biases, yet it’s challenging to ascertain how or why they behave a certain way in specific situations,” she noted.

While Cooper found the LinkedIn experiment “frustrating,” she believes it mirrors broader social biases. “I’m not disillusioned with the platform; I’m more dissatisfied with the lack of progress in society.”

User discusses LinkedIn’s hybrid role as both a business and a social network, a trend that has emerged since the pandemic blurred professional boundaries and normalized oversharing in the workplace. LinkedIn often encourages extreme “peer coding.” The platform’s most visible accounts highlight the extremes of this behavior here.

These recent “bro-coding” experiments stem from what Cornish, Bonnet, and others suggest is an algorithm shift that has notably lessened female creators’ visibility. This spurred a series of informal experiments earlier this year, where women and men across similar industries posted identical content, revealing significant disparities in reach.

What purpose does LinkedIn serve? An AI system categorizes posts according to content and the professional identity and skills of the user to determine their spread. The company claims to routinely assess its algorithms, including “monitoring for gender-related disparities.”

A spokesperson from LinkedIn indicated that the recent reduction in reach for some users may be attributed to a significant increase in content on the platform, noting that comments surged by 24% over the past quarter, alongside a proportional rise in video uploads.

In Bonnet’s perspective, “peer coding” is on the rise. “While people once viewed LinkedIn as a more sophisticated, business-focused space, that perception is fading. It’s rapidly becoming the Wild West.”