Patterns of representation and discrimination in dating applications: Analysis and perspectives

Dating applications have transformed the dynamics of social interaction, influencing users' self-representation and the construction of identities in digital environments. Platforms such as Tinder, Bumble, and Grindr not only facilitate encounters but also operate through algorithms that determine profile visibility and prioritization. However, these systems are not neutral, as they can reinforce stereotypes and biases, limiting the representation of certain groups and affecting the perception of diversity within these spaces. This study analyzes how algorithmic models on these platforms influence patterns of representation and discrimination, exploring their implications for equity and diversity in digital interactions. Through a critical literature review, the article examines two main axes: (1) the representation of diversity on these platforms and (2) discrimination and exclusion within their operation. The study concludes that the automation of these processes can amplify unconscious biases and restrict diversity in digital socialization, highlighting the need for strategies to mitigate these effects and promote greater equity in digital representation.