Attention economy

On dating platforms, attention is scarce. It is asymmetrically distributed — and it follows a mechanism that the participants themselves keep reinforcing.

Concentration on a few profiles

From the extreme distribution of likes follows a concentration on a small peak: the top 10 % of male profiles capture about 58 % of the likes given by women; the bottom 50 % together receive about 4.3 %. [3] On the female side the distribution is less steep but also unequal — the more common question there is not “will I be seen?” but “how do I filter who reaches my inbox?”.

Signal loss through mass swiping

When a like no longer signals scarce effort, it loses its informational value. That is what has happened in the attention economy of the apps: a right-swipe rate of ≥ 40 % on the sending side reduces the diagnostic value of an individual like to near zero. On the receiving side a like is no longer read as “this person chose me” but as “this person may have chosen everyone”. The signal loss shows up in reply rates to first messages (see communication & ghosting).

Cognitive overload

The paradox of choice — that as the number of options grows, decision capacity and satisfaction with the chosen option decline — is empirically documented for dating apps. [34] The interface’s suggestion of infinite candidates (“there is always a subjectively better profile one swipe away”) undermines the willingness to commit to any concrete person.

The result: a state of emotional exhaustion known as “swipe fatigue”. Industry and media data 2024/2025 put the share of affected users in younger cohorts at roughly 79 % (Gen Z) and 80 % (Millennials). [8]

Feedback loop

From the uneven distribution emerges a self-reinforcing loop:

1. Men reduce selectivity to raise the statistical match probability.
2. The meaning of any single like decreases; women raise their selectivity as a defense mechanism.
3. Men experience falling match rates and reduce selectivity further.
4. Algorithmic platforms tighten visibility of unselective senders (spam signal).

The loop is not an algorithmic mistake but a structural consequence of the two-sided market. Platforms like Hinge try to break the loop by forcing effort (likes only on a specific prompt/photo). Data show this materially raises match probability per like; 90 % of Hinge matches turn into actual conversations — compared with platforms where matches mostly languish unused in the inbox. [3]

Not normative

This description does not judge either side. Both patterns are rational responses to an architecture that cheapens every gesture. Anyone who wants to change the attention economy of the apps starts not at the user, but at the friction level of the interface.