Preferences of Mobile Dating App Users: A Semantic Network Analysis Approach

Abstract

Historically, differences have existed between heterosexual men and women regarding the traits they value most in a potential romantic partner. For example, men have typically prioritized their partner’s physical attractiveness, while women have typically valued job stability and income. These differences in partner selection between men and women have persisted in multiple studies of both traditional dating and online dating, even though other dating norms have changed in the past few decades. The most recent trend in dating is the use of mobile dating apps, but researchers have yet to examine whether these gender differences persist on this new platform. My study attempts to address this information gap by using a semantic network analysis approach combined with frequency distributions to investigate whether gender differences in partner selection are still present when interactions occur via mobile dating apps. Results indicate that men and women value similar attributes when assessing someone’s mobile dating app profile; both groups highly valued potential partners’ physical attractiveness, although women participants using mobile dating apps also prioritized partners’ intelligence and college major. Future research is required to determine whether gender differences in partner preference are disappearing across all forms of dating or if these results are specific to the platform (i.e., the use of a mobile dating app). Because this sample was limited to cisgender college students from a single Midwestern university, future research should also target a more diverse group of participants across age, gender, sexuality, and ethnicity to determine whether these results are generalizable.