Intersectional hate

When hate targets all of who you are.

For people at the intersection of multiple marginalised identities, online abuse is more than the sum of its parts. Fendr is built around you as a whole person, not a single category.

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Hate doesn't come in clean categories.

Online hate is often discussed in categories, racism, homophobia, antisemitism, misogyny, islamophobia. The systems built to detect and remove it are organised around those same categories. But for many people, hate doesn't come in clean categories.

A Black queer person doesn't face racism in one comment and homophobia in the next. The abuse targets both at once, in language specifically designed for that intersection, drawing on racist tropes about queer Black people, or homophobic abuse inflected with racial hostility, in ways distinct from either alone.

A Muslim woman wearing hijab faces islamophobia and misogyny simultaneously. A Jewish woman faces antisemitism and misogynistic targeting that compounds in specific ways. A trans woman of colour faces racism, transphobia, and misogyny layered into abuse that targets all three at once.

This compounding is not just more hate. It is qualitatively different hate, often more intense, more specific, and harder to process because it's harder to name. And it's what generic systems handle worst.

Why generic tools fail here.

Most automated hate detection is built around categories. A system trained on racial slurs catches racial slurs. A system trained on homophobic language catches homophobic language. The assumption is that these operate independently, that you're either targeted for your race or your sexuality, not for the specific intersection of both.

That assumption is wrong, and it has consequences. Abuse targeting the intersection of two identities may not trip either individual category filter cleanly. The language may be coded in ways that only make sense in the context of both identities, using in-group references immediately recognisable to anyone at that intersection but invisible to a keyword system.

When comments targeting multiple aspects of someone's identity are left visible, they signal to everyone who visits that this layered abuse goes unchallenged. Removing it in real time changes what the profile communicates to everyone who holds more than one marginalised identity.

How Fendr approaches this differently

Fendr is built around you as a whole person. Not your race. Not your sexuality. Not your religion. All of it, together, in the context of who you are and what you face. When you tell Fendr who you are, you describe your full identity, and it builds your protection profile around that whole picture.

Whole-person protection

Built around your full identity, not a single category.

Context-aware detection

Understands abuse that operates at the intersection of multiple identity dimensions, including coded language that only makes sense in that specific context.

No forced categorisation

Fendr doesn't require abuse to fit a single label to catch it.

Removes what single-axis systems miss

Particularly the coded, layered abuse that targets people at the intersection of multiple marginalised identities.

Removed in real time

Your audience never sees it, and every action is logged for you to review or reinstate.

Full control, always yours

Everything logged and reviewable, on your terms.

How it works

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Connect your Instagram

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Tell Fendr who you are

Your content, your identity, the abuse you face. Fendr builds around you, not a generic filter.

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Stay protected

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Protection built around all of who you are.

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When Hate Targets Multiple Parts of Who You Are | Fendr