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Online dating consumer preferences

For general social networks, gender differences lead to obvious differences in behaviors and preferences between men and women.Research on an online-game society showed that females perform better economically and are less risk-taking than males, and they are also significantly different from males in managing their social networks [].

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We find that for women, network measures of popularity and activity of the men they contact are significantly positively associated with their messaging behaviors, while for men only the network measures of popularity of the women they contact are significantly positively associated with their messaging behaviors.Marriage market is the first stage of a multi-stage game and corresponds with the Pareto efficiency of equilibrium.In the Internet age, Lee and Niederle launched a two-stage experiment in online dating market using rose-for-proposal signals [].The likes-attract means that people choose mates who are similar to themselves in a variety of attributes, which is consistent with the Chinese saying “men dang hu dui”.From the perspective of evolutionary and social psychology [].The users’ profiles include 35 attributes, such as user ID, gender, birthday, education level, mate requirements and so on.

The dating site requires the registered users to be at least 18 years old at the time of registration, thus on the platform the minimum user age is 18.

There are three data tables in the dataset, including female profiles, male profiles and the user behavior data.

There are total 548,395 users in the dataset including 344,552 male users and 203,843 female users.

In other words, men tend to seek young and physically attractive women, while women pay more attention to men’s socio-economic status [].

In fact, analyzing gender differences of online identity reconstruction in an online social network revealed that men value personal achievements more while women value physical attractiveness more [].

To address the research gap, in this paper, using empirical data from a large online dating site in China, we explore the users’ attribute preference compared with random selection, and use logistic regression to study how the users’ demographic attributes, popularity and activity and compatibility scores are associated with messaging behaviors, which reveal the gender differences in potential mate selection.