Kwon, Soonjae, Gene Moo Lee, Dongwon Lee, Sung-Hyuk Park (2024) “Seeing the Unseen: The Effects of Implicit Representation in an Online Dating Platform,” Working Paper.
- Previous title: Learning Faces to Predict Matching Probability in an Online Dating Market
- Presentations: DS (2021), AIMLBA (2021), WITS (2021), ICIS (2022)
- Preliminary version in ICIS 2022 Proceedings
- Based on an industry collaboration
This study investigates the effects of implicit preference-based representation on user engagement and matching outcomes in two-sided platforms, focusing on an online dating context. We develop a novel approach using explainable AI and generative AI to create personalized representations that reflect users’ implicit preferences. Through extensive matching simulations, we demonstrate that implicit representation significantly enhances both user engagement and matching outcomes across various recommendation algorithms. Our findings reveal heterogeneous effects driven by positive cross-side and same-side network effects, which vary depending on the gender distribution within the platform. This research contributes to understanding implicit representation in two-sided platforms and offers insights into the transformative potential of generative AI in digital ecosystems.