The Dalloway
Project
Read the evidence

Live editorial index

The Dalloway Observatory

Instrument 01 / Live estimate

The state of
human connection.

A live investigation into dating apps failing in the UK, the algorithms that shape attraction, and what loneliness in London reveals about the search for connection.

By The Dalloway Project
Updated / 18 min read

Estimated UK dating-app sessions ending without a match since you arrived

000,000

Every second, another conversation that never happened.

−594,000Tinder users
−368,000Bumble users
−131,000Hinge users

UK audience change, May 2023 to May 2024. Source: Ofcom, Online Nation 2024 archive.

How the estimate works +

This is a model, not a live feed from the apps. It starts with the widely reported figure of 1.6 billion Tinder swipes a day globally and uses a conservative 1% match-rate ceiling. We estimate a 6% UK share from 4.5 million active UK users against roughly 75 million active users globally, then assume 100 swipes in a session. That gives about 11.1 UK sessions without a match each second. “Session” and “swipes per session” are not published by Tinder, so the clock makes its assumption visible rather than presenting the result as observed fact.

Instrument 02 / Product anatomy

The Algorithm
Autopsy

The claim that dating products are “designed to keep you single” is too neat. Their incentives are more awkward than that. A useful match may help the product. A relationship may remove two users. The machinery is built to keep producing choices while connection asks people to stop choosing.

01

Ranking
Desirability

Tinder: a score is not chemistry

Tinder once described an internal Elo-style score. In its simplest form, a swipe from someone rated highly could raise your score more than a swipe from someone rated lower. It was a ranking system for desirability, not a psychological model of compatibility. Tinder says it stopped relying on Elo years ago; its public account now emphasises activity, proximity, preferences and signals such as likes and passes.

The distinction matters. A Tinder algorithm can learn who tends to approve of your profile. It cannot observe the ease of a conversation, the generosity of an interruption, or how two nervous people alter each other's pace in a room. Probability of a right swipe is a useful ranking target because it creates visible activity. It is not the same target as a relationship. The screen collapses both into one gesture, then invites us to confuse the gesture with knowledge.

Read the record: Tinder's earlier Elo score and Tinder's account of its current matching signals.

Observed signalRanked output
9.2High approval probability
7.4Likely right swipe
?You, reduced to signals
4.1Low predicted action
LIKELY TO SWIPELIKELY TO CONNECT
Exhibit A / A ranking can predict approval. It cannot observe chemistry.
02

Recommendation
Feedback

Hinge: designed to be measured

The Hinge algorithm uses stated preferences, behaviour and feedback to order recommendations. Its Most Compatible feature has been described through the Gale-Shapley matching problem: a way to suggest a pair whose preferences appear mutually promising. “We Met” feedback can add a post-date signal. This is more considered than a pure popularity score, and the stated ambition, “designed to be deleted”, is unusually clear.

But the app still needs measurable actions. Likes sent, matches made, replies and return visits are legible. The quality of a silence on a first date is not. Publicly available evidence does not prove Hinge simply optimises time in app, and it would be careless to say it does. The structural tension is enough: product teams can test engagement quickly, while a good relationship happens slowly and mostly off-screen. The promise points outward. The dashboard points back at the product.

Product record: Hinge's maintained help centre. Current research: decision-making on dating apps.

THE RELATIONSHIP?Happens beyond the dashboard
Exhibit B / The promise exits the loop. The metrics remain inside it.
03

Expiry
Pressure

Bumble: the anxious clock

Bumble's heterosexual matching design originally required women to open the conversation, with a match expiring after 24 hours if no message arrived. Opening Moves has since softened that rule by allowing a pre-set question that a match can answer. The expiry clock remains part of the product's grammar: make a choice now or lose the possibility.

A deadline can prevent a match list becoming a museum of abandoned intentions. It can also turn ordinary life into a signal of rejection. Work ran late. A notification disappeared. Someone needed a day to decide what to say. The Bumble algorithm does not need to understand any of that; the interface simply converts elapsed time into closure. Urgency produces action, but action under threat of expiry is not necessarily attention. The clock makes hesitation look like failure when hesitation may be the most human thing in the exchange.

Read the record: Bumble's explanation of messaging and expiry.

2418120600
A POSSIBILITYtime passesA VERDICT
EXPIRED
Exhibit C / The interface turns ordinary delay into apparent rejection.
04

Removal
Chat

Breeze: move the uncertainty

The Breeze dating app removes the chat phase. If two people like each other, they arrange and pay toward a real date. This is an intelligent answer to a familiar failure: lively matches that become flat message threads, then nothing. Breeze makes intention costly enough to be credible and moves the meeting into the world.

Removing chat solves the problem of endless chat. It does not design the date itself. Two strangers still arrive with little shared context, carrying the evaluative pressure that the interface was meant to escape. The venue, the prompt, the exit and the expectation now do the work the message thread used to do. That may be better. It is not neutral. Breeze demonstrates an important principle for IRL dating London experiments: when a product removes one stage, its emotional labour does not vanish. It moves downstream.

Product record: Breeze's maintained product site. The removed BBC Worklife article is no longer used as evidence.

CHATUNCERTAINTYGHOSTING
×NO CHAT
DATEPRESSURENO CONTEXT

THE FRICTION WAS NOT DESTROYED.
IT CHANGED LOCATION.

Exhibit D / Removing a stage moves its emotional labour downstream.
05

Compatibility
Room

Haystack: a good shortlist enters a bad room

Haystack dating events use a pre-event questionnaire to identify potentially compatible people before they meet. It is a sensible correction to the arbitrary guest list. In principle, the algorithm narrows a room without asking attendees to perform the narrowing themselves. BODA dating and Someone's Type London also sit within a broader return to curated or in-person alternatives, each making a different wager on selection and context.

But matching can only decide who enters. It cannot decide what the room rewards once they arrive. If everyone is pushed through brief, interview-shaped encounters, potentially compatible people may still meet as compressed versions of themselves. The questionnaire has done its job; the environment can undo it. Compatibility is not a parcel the algorithm delivers. It is a possibility that the format can reveal, distort or leave untouched.

VALUESHABITSINTENTTYPE
COMPATIBILITY
LOUD OPEN MIXER
GOOD INPUTSA REVEALING ROOM
Exhibit E / The algorithm chooses the guest list. The format decides who becomes visible.
06

Constraint
Mixer

Thursday: half a revolution

Thursday dating London events turn app attention into a time and a place. The app's original constraint was temporal, operating one day a week; its events make the escape from messaging literal. People who are tired of managing a parallel romantic inbox can at least encounter one another in full scale.

Removing the app from the decisive moment solves half the problem. Keeping the mixer format retains the other half. A loud open room still rewards rapid assessment, easy confidence and the ability to interrupt. It gives little structure to the person who becomes interesting through action, disagreement or a second encounter. Thursday proves demand for meeting offline. It does not, by itself, prove that the familiar singles mixer is the best container for that demand. Leaving the screen matters. What people enter next matters just as much. The project is looking for the other half.

Product record: Thursday's maintained product and events site.

01THE SCREENREMOVED
02THE MIXERUNCHANGED?
HALF THE PROBLEM
IS STILL THE PROBLEM.
Exhibit F / Moving offline matters. The structure waiting there matters too.
Conclusion / Product autopsyCause of failure

The algorithmis not the problem.

The algorithmis the symptom.

Every one of these products is trying to solve connection with a tool designed for efficiency.

EFFICIENCYCONNECTION

A note on limits: product algorithms change, and companies do not publish every ranking signal. This autopsy distinguishes documented mechanics from our interpretation of their incentives. It is an argument, not an audit of private code.

The finding / 01

London does not have a shortage of single people.

It has a shortage of conditions in which people can become visible to one another.

Instrument 03 / The reading room

The evidence
deserves its own room.

The Human Connection Index now lives with the Field Notes: 57 checked records across academic research, government data, journalism and the project’s own arguments.

Open the Human Connection Index

Instrument 04 / Private calculation

The Time Machine.

What did dating apps actually cost you?

How long have you been on dating apps?

Your age is used only for this page’s calculation. It is never saved.

Estimated time spent swiping

34days of your life
136 books408 films326 Paris trips0.7 conversational languages816 hours of conversation

That is 136 books, 326 trips to Paris, or most of a conversational French.

Calculated privately in your browser. Nothing is stored.

The app knew six things about you the whole time. None of them explain why you kept coming back.

The room is a different use of an evening. See what is in progress

Instrument 05 / An honest look under the hood

The Dating MOT.

A standard MOT has three outcomes. Pass. Advisory. Fail. This one has three too, but nothing fails. Things are working, worth watching, or worth changing.

Not a judgement. A read.

01The apps

Which have you used?

02IRL

What kind?

03The honest questions

Reading the evidence

Four questions
the numbers cannot answer alone.

01

Why are dating apps failing in the UK?

+

Falling audiences do not prove that every dating app fails every user. They do show fatigue. Ofcom recorded substantial UK audience losses for Tinder, Bumble and Hinge between May 2023 and May 2024. Swipe interfaces optimise actions they can measure, while durable connection develops mostly beyond the screen.

02

Do dating app algorithms keep people single?

+

There is no public evidence that major dating apps explicitly instruct their algorithms to prevent relationships. The structural tension is subtler: engagement is immediately measurable, while a successful relationship may remove users from the product. The algorithm can rank observable behaviour; it cannot fully evaluate a life built outside it.

03

Are IRL singles events better than dating apps?

+

Meeting in person restores voice, timing, movement and behaviour. But an unstructured mixer can reproduce the same rapid assessment as a swipe interface. Better IRL dating in London depends on the format: what people do together, how pressure is distributed and whether interest gets more than one moment to form.

04

Is loneliness increasing in London?

+

London evidence shows loneliness is real but unevenly distributed, shaped by age, income, housing, health and belonging. A city can offer constant proximity without repeated contact. Read our Field Note on loneliness in London or search the government and academic evidence above.