Objective data online dating
(Which also creates the possible complication for Tinder work itself as they claim to have the ranking system which influences which users are being shown to whom based also on how much are they liked by others.
It cannot be considered reliable based on matches from males who swipe right every profile they see.)So my research from before can be considered relevant only in part of counting my own attraction to males, while the second experiment shows not my attractiveness in different contexts, but strategies of males.
Consequently, it is clear that little information is being imparted in opening conversations.”*note that expectations and strategies are based on the self declared questionnaires, not objective data, which raises questions of people being honest, people realizing their intents, being capable of measuring it, etc.
Most interesting finding for me was directly related to the strategies of users and my own previous research: In a sense that instead of measuring attractiveness of the certain user it actually shows the blend of strategies by male users in certain context — if all male users swipe all females they see, there is no way to understand certain female performance.
What happens on the female side is that women put effort into carefully selecting the men they like, get match with them, but no further communication happens as after receiving match that man could have decided that he doesn’t like this woman.
Charlie Stelle, have been researching the landscape and found that people over 60 represent the most rapidly growing demographic in online dating.
You can read an article about the ongoing study by clicking here.
Most of all, how it raises very interesting question on whether the open-format profiles model of Tinder is functional at all and really works for users.
First, what fascinated me is how the complex research with a lot of data analysis involved is confirming all the qualitative empirical observations that one can get by using service and talking to people.