Exploring Gender Disparities in Bumble's Match Recommendations

Mixed-methods study revealing algorithmic gender disparities in dating recommendations in India

This project investigates algorithmic bias in a large-scale dating platform, combining quantitative analysis and qualitative insights to surface gendered disparities in recommendations.

Authors: Ritvik Aryan Kalra, Pratham Gupta, Ben Varghese, Nimmi Rangaswamy
Venue: 15th Annual AIS SIG GlobDev Pre-ICIS Workshop (Dec 2023)

Links:

arXiv
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References

2023

Exploring Gender Disparities in Bumble’s Match Recommendations

Ritvik Aryan Kalra, Pratham Gupta, Ben Varghese, and 1 more author

Dec 2023

15th Annual AIS SIG GlobDev Pre-ICIS Workshop

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We study algorithmic bias in a large-scale, real-world dating platform in India, combining quantitative analysis and qualitative insights to surface gendered disparities in recommendations and discuss implications for inclusive system design.