Are Dating Apps Hiding Black Women? What the Experiments Show

The Dating News Flag is a term coined by Overstand Dating on July 16, 2026.

TLDR: Black women have been running an experiment on Hinge and the results keep coming back the same: change your race to white and the pool improves, the likes multiply, and the men who suddenly appear are more educated, more employed, and more engaged. Same face. Same photos. Same prompts. Different race box. The Washington Post covered it. The Root covered it. TikTok is full of it. Sociologist Apryl Williams of the University of Michigan spent nearly a decade researching it and wrote an entire book on the conclusion: dating apps automate sexual racism and make it routine. No platform has fully addressed it.

Table of Contents

• What the Experiments Show
• This Is Not New Data
• How the Algorithm Works Against You
• What the Platforms Have Said
• The Research Behind the Experience
• What Black Women Are Actually Doing About It
• The Dating News Flag Verdict

You built a real profile. Good photos. Actual prompts. An honest bio. You have a career, a personality, and a clear sense of what you want. You are getting maybe one like a week, if that. The men in your feed look like a different category of person than what you see on a friend's screen.

Then you hear about the experiment. You change your race to white. Overnight, you get ten likes. The men in your feed have degrees and jobs and profiles that look like someone who actually tried. Nothing else changed.

That is the experience Black women have been documenting, publicly and in detail, for years. And the more it gets documented, the harder it is to look away.

Before you keep swiping on a platform that may not be serving your profile fairly, run it through ProfileFlags to check what signals your profile is actually sending. One scan, $19.99. Know what you are working with before the algorithm writes your story.

What the Experiments Show

In July 2024, a Black woman in Los Angeles wrote about her experience for The Cut. She had been using Hinge's paid version, going on two to three dates a week, and feeling like she kept seeing the same pool of men recycled back. She saw a TikTok from another Black woman who said changing her race to white on Hinge changed her results. She tried it.

The difference was immediate. Men who had only been appearing in Hinge's premium "Standouts" section, which the app describes as "outstanding content from people most your type," were suddenly appearing in her regular feed. The men were, by her account, more attractive, better educated, and better employed. She ran the same experiment on Bumble, which does not use race as a matching variable, and saw no change.

Hinge's response when she reached out: "We show you who you are most likely to want to go on a date with, and who is likely to want to go on a date with you."

That quote is doing a lot of work.

In April 2026, The Root covered TikTok creator @cityvibeswithMarie, a 36-year-old woman with an MBA who had been on Hinge for two and a half weeks with zero matches. At her followers' suggestion, she changed her race from Black to white and documented what happened over 22 days.

Within 24 hours: likes went from one per day to ten. A 10x increase.

The men she was now seeing across all races had advanced degrees or strong careers. That was not what her feed had shown before, despite her own MBA-level profile. By day 22, she had her first match. Her hypothesis, stated directly: "There is bias built into the algorithm that is systematically deprioritizing Black women."

In 2024, TikTok user @bodaciousboho ran a controlled version. Two Hinge accounts. Same photos. Same prompts. Same everything. One listed race as Black. One listed race as white. The white profile massively outperformed the Black one.

"This app is not for Black women," she said. "It's not just the fact that people prefer white women. It's the fact that this algorithm is pushing white women more than it is Black women. This is systemic."

Journalist Anita Bhagwandas, writing on Substack in January 2025, ran the same test as a South Asian woman. After changing her ethnicity to white on Hinge, her matches expanded to include men of all races. Before the change, she was almost exclusively matched with men of her own background despite having her preferences set to open.

These are not isolated stories. They are consistent findings across different women, different cities, and different years.

This Is Not New Data

The foundation of this problem goes back further than TikTok experiments.

In 2009 and again in 2014, OkCupid released internal user data. The findings, widely covered and cited since, showed that 82% of non-Black men on the platform exhibited measurable bias against Black women in their rating behavior. Black women were rated as less attractive than women of other races by men across racial groups, with Black men being the exception.

OkCupid co-founder Christian Rudder published some of that data himself. The platform that generated the data did not fix the problem. The data was used as a talking point. The pattern continued.

A 2024 peer-reviewed study published through Tandfonline examined racial preferences in dating app behavior using an experimental approach and found documented patterns of racial boundary enforcement, with white women presented more favorably across the system.

The question is not whether racial bias exists in dating apps. That has been established for over a decade. The question is whether the platforms are amplifying it.

How the Algorithm Works Against You

Dating apps do not show every profile to every user. They rank, sort, and decide who sees whom.

Tinder used to operate on what it called an ELO score, a desirability rating borrowed from chess, that ranked users based on how others swiped on them. If users with high scores swiped left on your profile, your score dropped. If low-scoring users swiped right, it did not help much. Tinder has since said it moved away from that system, though it has not been fully transparent about what replaced it.

Hinge has not disclosed its algorithm in detail. What it has said publicly is that it tries to show you people you are "most likely to go on a date with" and vice versa. That framing is the problem. If years of user behavior data tell the algorithm that Black women receive fewer likes from certain groups, the algorithm learns to show Black women to fewer people, or to lower-desirability pools, because that is what the data says will produce a "match."

This is the feedback loop Apryl Williams described to Harvard Gazette in April 2024: the algorithm reflects and then reinforces existing racial bias. It does not introduce the bias. It codifies it, speeds it up, and makes it feel like a neutral, personalized result.

Professor Orly Lobel, author of The Equality Machine, told the Washington Post in October 2024 that most dating apps factor ethnicity into their algorithms and can promote racial bias even when that is not their intention. The problem is not necessarily malice. It is the unexamined consequence of training a machine on biased human behavior and calling the output a recommendation.

What the Platforms Have Said

Hinge has not issued a substantive public statement on the pattern documented across multiple outlets and years of user testimony.

When The Cut contacted Hinge in 2024, a spokesperson said the app shows users "who you are most likely to want to go on a date with and who is likely to want to go on a date with you." That is a description of the algorithm's intent. It is not an acknowledgment that the algorithm may be encoding racial preference as a signal for desirability.

No major dating platform has released race-disaggregated data on match rates, like rates, or profile visibility. The companies that profit from the problem own the data that could prove or disprove it. They have not shared it.

The Research Behind the Experience

Apryl Williams is a sociologist and assistant professor at the University of Michigan. She is also a faculty associate at Harvard's Berkman Klein Center. She opened a Tinder account in 2013 and spent nearly ten years researching what she found. In 2024, she published Not My Type: Automating Sexual Racism in Online Dating.

Her finding, stated plainly during a Harvard Gazette interview: "What dating apps do is automate sexual racism, making it hyper efficient and routine to swipe in racially curated sexual marketplaces."

Williams argues that dating apps rely on white heteronormative standards of attractiveness and desirability to power their sorting systems. The apps did not create those standards. But they embedded them into code, scaled them to millions of users, and made them feel like personalized results rather than cultural bias running at algorithmic speed.

Her experience is both academic and personal. She met her partner on Tinder in 2021 and is now married. Her point is not that the apps are unworkable. It is that they are broken in specific, documented ways for specific groups, and the platforms have not been transparent about it or accountable for it.

Williams also noted, during the Harvard event, that she requested her own data from the apps. What she got back included geolocation history, every photo she had uploaded, every linked interest from her Facebook account, and every conversation she had ever had. The apps have detailed data on behavior, race, and outcomes. They are choosing not to share the part that would answer the question.

For more on how digital patterns in dating get weaponized, see Did You Fall for Them. Or Their AI? and The New Rules of Dating in the AI Era.

What Black Women Are Actually Doing About It

Beyond the experiments, Black women are making practical decisions.

Some have removed their race from their profiles entirely. Reddit threads in r/hingeapp from March 2026 document Black women switching their ethnicity to "other" and seeing their results shift. Some are leaving Hinge altogether and reporting better results on Bumble, where race is not used as a matching variable in the same way.

Others are documenting everything publicly, as @cityvibeswithMarie did, and building a record that cannot be explained away as individual preference. One lawyer commented on her videos urging her to consider legal action and calling her data set potentially valuable as evidence.

And some are choosing to opt out of the app ecosystem entirely and invest in dating tools that work differently. MyDatePage is built on the opposite premise: your profile exists on your terms, with your full story, not filtered through an algorithm trained on who gets the most swipes. It is not a fix for the systemic problem. It is a way to take back some control over your own presentation.

There is also the question of what to do when you are still on the apps. ProfileFlags analyzes your profile for patterns, signals, and flags before you keep pouring time into a platform that may not be distributing your profile fairly. Know what your profile actually communicates before you accept that the results reflect your worth.

The Dating News Flag Verdict

The pattern is documented. Multiple women. Multiple cities. Multiple years. Multiple platforms, with Hinge producing the most consistent results. Peer-reviewed research. A book from a Harvard-affiliated sociologist. A Washington Post investigation. And zero meaningful transparency from the platforms involved.

The question of whether this is intentional design or an unexamined feedback loop may matter legally. It does not change the daily experience of a Black woman who built a real profile, is getting one like a week, and now knows that changing a single data field produces ten times the engagement overnight.

That is not a preference problem. That is an infrastructure problem.

Dating apps are not neutral tools. They are sorting systems built on data generated by people who carry cultural biases, and the companies running them have had years and a growing stack of evidence to audit their systems. They have not done it.

Until they do, the most useful thing is to know the problem exists, document it when it happens to you, and stop interpreting poor app results as a verdict on your desirability.

They are not the same thing.

This post is for general information and public interest reporting on documented trends in online dating. It is not legal advice. Sources: The Cut (July 2024); The Root (April 2026); Washington Post (October 2024); Harvard Gazette interview with Apryl Williams, University of Michigan (April 2024); Apryl Williams, Not My Type: Automating Sexual Racism in Online Dating (2024); OkCupid user data (2009, 2014); Tandfonline, Racial preferences in dating apps: an experimental approach (May 2024); Anita Bhagwandas, Substack (January 2025); Orly Lobel, The Equality Machine, via Washington Post.