Price of Anarchy in Algorithmic Matching of Romantic Partners
Andr\'es Abeliuk, Khaled Elbassioni, Talal Rahwan, Manuel Cebrian,, Iyad Rahwan

TL;DR
This paper analyzes how self-interest in online dating platforms impacts social efficiency, using game theory to quantify the price-of-anarchy and demonstrating that competition can improve overall matching quality.
Contribution
It introduces a theoretical framework to bound the price-of-anarchy in online dating, and empirically shows that competition aligns agents' interests with social welfare.
Findings
Price-of-anarchy is bounded by a constant independent of user base size.
Competition among dating sites improves social welfare.
Selfish matching algorithms can be mitigated through market competition.
Abstract
Algorithmic-matching sites offer users access to an unprecedented number of potential mates. However, they also pose a principal-agent problem with a potential moral hazard. The agent's interest is to maximize usage of the Web site, while the principal's interest is to find the best possible romantic partners. This creates a conflict of interest: optimally matching users would lead to stable couples and fewer singles using the site, which is detrimental for the online dating industry. Here, we borrow the notion of Price-of-Anarchy from game theory to quantify the decrease in social efficiency of online dating sites caused by the agent's self-interest. We derive theoretical bounds on the price-of-anarchy, showing it can be bounded by a constant that does not depend on the number of users of the dating site. This suggests that as online dating sites grow, their potential benefits scale up…
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Taxonomy
TopicsSexuality, Behavior, and Technology · Marriage and Sexual Relationships · Demographic Trends and Gender Preferences
