China’s Social Credit Systems: An Analysis of the Mate Selection Process of Chinese Women

The latest events of establishing Social Credit Systems (SCSs) in China have received much attention, not only locally, but also on the international level. A lot has been written about the SCSs, putting the focus on the construction of big data platforms, surveillance control mechanisms and the reputational system etc. However, its social impact and its functions in the dating market in today’s China is an understudied topic. Its operation of selecting people by means of ‘value’ predicts major changes in the realm of the social fabric, such as the mate selection process of Chinese women. Today, women are still torn between traditional family patterns and their own choice concerning mate selection. From now on, women might have to take a third component into account, namely the integrity of their future life partner in terms of the SCSs. Using qualitative data of surveys and interviews, this dissertation investigates the influences of the SCS pilots in regard to the mate selection process of urban Chinese women to find out to what extent the SCSs have an impact on the partner selection in China

Gender-specific preference in online dating

Abstract In this paper, to reveal the differences of gender-specific preference and the factors affecting potential mate choice in online dating, we analyze the users’ behavioral data of a large online dating site in China. 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. Secondly, when women send messages to men, they pay attention to not only whether men’s attributes meet their own requirements for mate choice, but also whether their own attributes meet men’s requirements, while when men send messages to women, they only pay attention to whether women’s attributes meet their own requirements. Thirdly, compared with men, women attach great importance to the socio-economic status of potential partners and their own socio-economic status will affect their enthusiasm for interaction with potential mates. Further, we use the ensemble learning classification methods to rank the importance of factors predicting messaging behaviors, and find that the centrality indices of users are the most important factors. Finally, by correlation analysis we find that men and women show different strategic behaviors when sending messages. Compared with men, for women sending messages, there is a stronger positive correlation between the centrality indices of women and men, and more women tend to send messages to people more popular than themselves. These results have implications for understanding gender-specific preference in online dating further and designing better recommendation engines for potential dates. The research also suggests new avenues for data-driven research on stable matching and strategic behavior combined with game theory