Wikipedia:Reference desk/Archives/Mathematics/2024 April 20

= April 20 =

== Imagine one tinder gender has a max 100 right swipes per day and the other have X max right swipes per day. Would it be possible to find the value of X needed to make them have equal amount of matches with just that information? ==

Imagine one tinder gender has a max 100 right swipes per day and the other have X max right swipes per day. Would it be possible to find the value of X that would be needed to make sure they have equal amount of matches per day at average with just that information I am presenting here or you would need internal data to solve this mathematical problem?

75% of tinder is male, 25% is female.

Woman swipe right 7% of time while man swipe 40%

Woman match with 33% of man they swiped right while men match with 2.5% of person they swiped right.

Woman vote at 200 profiles per day while man do with 137. 179.134.97.227 (talk) 17:34, 20 April 2024 (UTC)


 * I'm not familiar with tinder, but it seems that the question is about a selection process for strictly binary and straight users, in which each of the two genders is only presented candidates of the other gender. Each candidate presented is a match for female users with probability 0.07 × 0.33 = 0.0231 and for male users with probability 0.40 × 0.025 = 0.0100&thinsp;.
 * Then the expected number of matches for a female user when presented 200 candidates equals 200 × 0.0231 = 4.62, while that for a male user when presented 137 candidates equals 137 × 0.0100 = 1.37&thinsp;.
 * So far so good, but where does the maximum of 100 come in if a woman can do 200 swipes per day?
 * Given match rates $p_{f}$ and $p_{m}$ for the two genders, the expected numbers of matches for users of these genders equal $n_{f}$ × $p_{f}$ and $n_{m}$ × $p_{m}$, in which $n_{f}$ and $n_{m}$ stand for the numbers of candidates presented to the respectively gendered users. To make these expected numbers equal requires achieving a ratio between these numbers of candidates such that
 * For the data supplied, this means,
 * $n_{f}$ : $n_{m}$ = 0.0100 : 0.0231 = 100 : 231&thinsp;.
 * So if female users are presented 100 candidates, male users need to get presented 231 candidates to achieve the same number of matches, to wit:
 * 100 × 0.0231 = 231 × 0.0100 = 2.31&thinsp;.
 * --Lambiam 20:33, 20 April 2024 (UTC)
 * At tinder, people are presented with a "random" (not exactly), person, they can swipe left (not like) or swipe right (like), if male A like female B and female B like male A they match and can start to talk. The 200 swipes means at average, the woman rates at this an day (like OR dislike) 200 people. Max amount of right swipes would be the amount of likes they would be able to give before not being able to give likes for that day. Woman receive way more matches than man at this apps for various reasons, the question here is if that information presented at the question, would be possible to find what would need to be the limit at the amount of likes a man can do (assuming woman can do 100 per day) to make sure the amount of matches is the same per day at average.179.134.97.227 (talk) 21:09, 20 April 2024 (UTC)
 * A question about your terminology. If male A likes female B and female B likes male A, which of the two "receives" the match? It seems to me that if every match is between two users of different genders, then each gender will always have the same number of matches as the other gender. A difference, if any, can only be in who initiated the process that led to the match being established. --Lambiam 21:18, 20 April 2024 (UTC)
 * "If male A likes female B and female B likes male A, which of the two "receives" the match? It seems to me that if every match is between two users of different genders, then each gender will always have the same number of matches as the other gender."
 * Man A and female B receive the match. A gender can have different numbers of matches at average, one example, if man 1 likes woman 1 and 2, man 2 likes woman 1 and 2, man 3 likes no one and woman 1 likes man 1 and woman 2 likes man 1. Thats man 1 having 2 matches and other man having no matches, thats 0.66 matches at male side and 1 match at average at the woman side.179.134.97.227 (talk) 21:30, 20 April 2024 (UTC)
 * Let $p_{m}$ stand for the number of matches under some procedure. In your example $p_{f}$ = 2, since we have the two matches man 1 ⇆ woman 1 and man 1 ⇆ woman 2. Let, furthermore, $n_{f}$ and $n_{m}$ denote the number of female and male users. In the example, $M$ = 2 and $M$ = 3. Then the average number of matches for the two genders are $u_{f}$ and $u_{m}$. In the example, we get $u_{f}$ and $u_{m}$. One way to get the two averages equal is to make sure that $M/u_{f}$ = 0, for example by not allowing any right swaps at all. The only other way does not involve the process for indicating preferences: make sure that $M/u_{m}$ = $2/2$.  --Lambiam 18:22, 21 April 2024 (UTC)
 * Let $2/3$ stand for the number of matches under some procedure. In your example $M$ = 2, since we have the two matches man 1 ⇆ woman 1 and man 1 ⇆ woman 2. Let, furthermore, $u_{f}$ and $u_{m}$ denote the number of female and male users. In the example, ⇭⇭⇭ = 2 and ⇭⇭⇭ = 3. Then the average number of matches for the two genders are ⇭⇭⇭ and ⇭⇭⇭. In the example, we get ⇭⇭⇭ and ⇭⇭⇭. One way to get the two averages equal is to make sure that ⇭⇭⇭ = 0, for example by not allowing any right swaps at all. The only other way does not involve the process for indicating preferences: make sure that ⇭⇭⇭ = ⇭⇭⇭.  --Lambiam 18:22, 21 April 2024 (UTC)