An empirical analysis of online dating

04 Apr

So for each dummy profiles, I computed: 1) His or her own popularity, (individuals who contacted him or her) 2) Ratings the physical attractiveness (according to their profile’s photos) of each user who contacted him or her. Then each user is sorted within a attractiveness group according to his/her rating obtained.

relieved of systemic constraint, which would otherwise limit their choices), female sexual choices will always tend towards small male breeding populations.

In more colloquial terms, what this means is that male/female ‘leagues’ are asymmetrical – with male ‘rank’ being bottom heavy in distribution, while female ‘rank’ being top heavy.

I worked with 4 highly attractive male profiles: 4 moderately attractive male profiles: 4 average-attractive male profiles: And 4 unattractive male profiles: Female profiles: 1 moderately attractive female (left), 1 highly attractive female (right): 1 unattractive female (left), 1 average attractive female (right): Since online sites (Badoo) do not provide the site’s activity log files to compute users’ popularity, as well as the popularity of their communication partners, (as measures of social desirability), I retrieved the number of messages by each fictitious profile to index his or her own popularity.

Next, I computed the mean popularity of the profile’s contacts.

A small amount of medium attractive females send some messages to moderately-attractive males. 4) Some unattractive female users contact moderately and medium attractive male daters (disassortative choice behaviour) We see that, the probability of sending a first-contact e-mail to a female profile is monotonically increasing in the attractiveness of the photo in that profile.